---------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/Wei/Dropbox/Twins/Restat-Twins/Data/Twins-data.log
  log type:  text
 opened on:  17 Aug 2015, 15:12:21

. use "$raw_path/1982dta", clear

. de

Contains data from /Users/Wei/Dropbox/Census/1982dta.dta
  obs:    10,012,474                          
 vars:            31                          18 Apr 2012 12:09
 size:   600,748,440                          
---------------------------------------------------------------------------------------------------------------------------
              storage   display    value
variable name   type    format     label      variable label
---------------------------------------------------------------------------------------------------------------------------
hhoftyp         byte    %8.0g                 
province        str2    %9s                   
prefec          str2    %9s                   
county          str2    %9s                   
commune         str7    %9s                   
hhcode          str3    %9s                   
persnnb         byte    %9.0g                 
brhnb81         byte    %9.0g                 
dthnb81         byte    %9.0g                 
persnnbA        int     %9.0g                 
id              float   %9.0g                 
namecode        str3    %9s                   
releahh         byte    %8.0g                 
sex             byte    %8.0g                 
age             int     %9.0g                 
nationty        byte    %9.0g                 
registat        byte    %8.0g                 
edulevel        byte    %8.0g                 
industry        int     %9.0g                 
occupation      int     %9.0g                 
noworkpn        byte    %8.0g                 
maristat        byte    %8.0g                 
chldborn        byte    %9.0g                 
chldlive        byte    %9.0g                 
bthord81        byte    %8.0g                 
houseid         float   %9.0g                 
housesize       byte    %9.0g                 
rural           byte    %9.0g                 
file            byte    %9.0g                 
nid             float   %9.0g                 
nhouseid        float   %9.0g                 
---------------------------------------------------------------------------------------------------------------------------
Sorted by:  

. gen prov = province 

. egen hhid = group(province-hhcode)

. keep hhid hhoftyp sex age releahh prov sex edulevel rural nationty chldborn chldlive

. de

Contains data from /Users/Wei/Dropbox/Census/1982dta.dta
  obs:    10,012,474                          
 vars:            11                          18 Apr 2012 12:09
 size:   160,199,584                          
---------------------------------------------------------------------------------------------------------------------------
              storage   display    value
variable name   type    format     label      variable label
---------------------------------------------------------------------------------------------------------------------------
hhoftyp         byte    %8.0g                 
releahh         byte    %8.0g                 
sex             byte    %8.0g                 
age             int     %9.0g                 
nationty        byte    %9.0g                 
edulevel        byte    %8.0g                 
chldborn        byte    %9.0g                 
chldlive        byte    %9.0g                 
rural           byte    %9.0g                 
prov            str2    %9s                   
hhid            float   %9.0g                 group(province prefec county commune hhcode)
---------------------------------------------------------------------------------------------------------------------------
Sorted by:  
     Note:  dataset has changed since last saved

. 
. keep if hhoftyp == 1 
(324103 observations deleted)

. drop hhoftyp 

. gen male = sex == 1 

. 
. drop if age > 120 
(1653 observations deleted)

. gen child = releahh == 3 

. egen child_num = sum(child), by(hhid)

. 
. * Have child
. drop if child_num == 0
(737490 observations deleted)

. gen boy = child& sex ==1 

. gen girl = child & sex ==2 

. 
. * Mother == 1 
. gen father = (releahh == 1 | releahh == 2) & sex == 1

. gen mother = (releahh == 2 | releahh == 1 ) & sex == 2 

. egen mother_num = sum(mother),  by(hhid)

. keep if mother_num == 1 
(400517 observations deleted)

. 
. * Mother birth age >= 15  
. gen f_age = age if father 
(7086395 missing values generated)

. gen m_age = age if mother 
(6841968 missing values generated)

. egen h_f_age = max(f_age), by(hhid)
(950183 missing values generated)

. egen h_m_age = max(m_age), by(hhid)

. gen c_age = age if child 
(3770528 missing values generated)

. egen h_c_age = max(c_age), by(hhid)

. drop if h_m_age - h_c_age <= 15
(45402 observations deleted)

. drop if h_m_age - h_c_age > 50 
(2327 observations deleted)

. gen m_birth_age = h_m_age - h_c_age

. drop h_c_age f_age m_age 

. 
. * Children number 
. gen n_chldborn = chldborn * mother 

. egen h_chldborn = max(n_chldborn), by(hhid)

. gen n_chldlive = chldlive * mother 

. egen h_chldlive = max(n_ chldlive), by(hhid)

. keep if h_chldborn == h_chldlive
(2650141 observations deleted)

. keep if h_chldborn == child_num
(1678472 observations deleted)

. drop n_chldborn h_chldborn n_chldlive  h_chldlive

. 
. * Children maximum age < 18 
. gen child_age = age if child 
(1884756 missing values generated)

. egen max_child_age = max(child_age), by(hhid)

. drop if max_child_age >= 18
(879411 observations deleted)

. drop max_child_age 

. 
. * father education, mother education
. gen f_edu = edulevel if father
(2652437 missing values generated)

. gen m_edu = edulevel if mother 
(2554766 missing values generated)

. egen h_f_edu = max(f_edu), by(hhid)
(338727 missing values generated)

. egen h_m_edu = max(m_edu), by(hhid)

. drop f_edu m_edu

. recode h_f_edu (6 = 1) (5 = 2) (4 = 3) (1/3 = 4)(. = 99)
(h_f_edu: 3292958 changes made)

. recode h_m_edu (6 = 1) (5 = 2) (4 = 3) (1/3 = 4)(. = 99)
(h_m_edu: 3292958 changes made)

. 
. * Ethnicity 
. gen f_han = nationty == 1 if father
(2652437 missing values generated)

. gen m_han = nationty == 1 if mother 
(2554766 missing values generated)

. egen h_f_han = max(f_han), by(hhid)
(338727 missing values generated)

. egen h_m_han = max(m_han), by(hhid)

. gen h_fm_min = h_f_han == 0 | h_f_han == 0 

. drop f_han m_han 

. 
. 
. * keep child data 
. keep if child 
(1575545 observations deleted)

. keep hhid sex age edulevel h_* child_num m_birth_age rural prov

. order hhid 

. sort hhid age

. cap drop twins 

. gen twins = hhid == hhid[_n-1] & age == age[_n-1]

. replace twins = hhid == hhid[_n+1] & age == age[_n+1] if twins == 0
(7263 real changes made)

. recode edulevel (6 = 1) (5 = 2) (4 = 3) (1/3 = 4)(. = 99)
(edulevel: 994095 changes made)

. 
. preserve 

. keep hhid age 

. duplicates drop 

Duplicates in terms of all variables

(7283 observations deleted)

. gsort hhid -age 

. bys hhid: gen order = _n 

. save "order82",replace
(note: file order82.dta not found)
file order82.dta saved

. restore

.  
. merge m:1 hhid age using   "order82"

    Result                           # of obs.
    -----------------------------------------
    not matched                             0
    matched                         1,717,413  (_merge==3)
    -----------------------------------------

. drop _merge 

. cap erase "order82.dta"

. gen year = 1982 

. count
1717413

. save "twins1982",replace 
file twins1982.dta saved

. 
. 
. *******************************************
. 
. use "$raw_path/census90",clear

. egen hhid = group(prov prefect county address house) 

. de

Contains data from /Users/Wei/Dropbox/Census/census90.dta
  obs:    11,475,065                          
 vars:            29                          18 Apr 2012 12:19
 size:   470,477,665                          
---------------------------------------------------------------------------------------------------------------------------
              storage   display    value
variable name   type    format     label      variable label
---------------------------------------------------------------------------------------------------------------------------
prov            byte    %9.0g                 
prefect         byte    %9.0g                 
county          byte    %9.0g                 
address         float   %9.0g                 
house           int     %9.0g                 
name            byte    %9.0g                 
relation        byte    %9.0g                 
sex             byte    %9.0g                 
age             float   %9.0g                 
nation          byte    %9.0g                 
regstat         byte    %9.0g                 
houstype        byte    %9.0g                 
usuresid        byte    %9.0g                 
usuresty        byte    %9.0g                 
migrate         byte    %9.0g                 
edulevel        byte    %9.0g                 
edustat         byte    %9.0g                 
industry        int     %9.0g                 
occu            int     %9.0g                 
nworksta        byte    %9.0g                 
maristat        byte    %9.0g                 
numbirm         byte    %9.0g                 
numbirf         byte    %9.0g                 
numsurm         byte    %9.0g                 
numsurf         byte    %9.0g                 
birth           byte    %9.0g                 
houset          byte    %9.0g                 
houssize        byte    %9.0g                 
hhid            float   %9.0g                 group(prov prefect county address house)
---------------------------------------------------------------------------------------------------------------------------
Sorted by:  
     Note:  dataset has changed since last saved

. 
. keep hhid nation prov prefect county address house houstype usuresty usuresid age relation edulevel numbir* numsur* sex

. de

Contains data from /Users/Wei/Dropbox/Census/census90.dta
  obs:    11,475,065                          
 vars:            18                          18 Apr 2012 12:19
 size:   321,301,820                          
---------------------------------------------------------------------------------------------------------------------------
              storage   display    value
variable name   type    format     label      variable label
---------------------------------------------------------------------------------------------------------------------------
prov            byte    %9.0g                 
prefect         byte    %9.0g                 
county          byte    %9.0g                 
address         float   %9.0g                 
house           int     %9.0g                 
relation        byte    %9.0g                 
sex             byte    %9.0g                 
age             float   %9.0g                 
nation          byte    %9.0g                 
houstype        byte    %9.0g                 
usuresid        byte    %9.0g                 
usuresty        byte    %9.0g                 
edulevel        byte    %9.0g                 
numbirm         byte    %9.0g                 
numbirf         byte    %9.0g                 
numsurm         byte    %9.0g                 
numsurf         byte    %9.0g                 
hhid            float   %9.0g                 group(prov prefect county address house)
---------------------------------------------------------------------------------------------------------------------------
Sorted by:  
     Note:  dataset has changed since last saved

. 
. gen urban_hukou = houstype == 2 

. gen resid_type = usuresty if usuresid == 1 
(1529976 missing values generated)

. egen resid_type_comm = mode(resid_type), by(prov prefect county address) minmode
Warning: at least one group contains all missing values or contains multiple modes.  Generating missing values for the mode
of these groups.  Use the missing, maxmode, minmode, or nummode() options to control this behavior.
(10674 missing values generated)

. drop resid_type 

. ren resid_type_comm resid_type

. drop prefect county address house

. drop if mi(resid_type)
(10674 observations deleted)

. 
. gen birth_year = int(age/100)

. gen birth_month = age - int(age/100)*100

. ren age birth_ym

. gen age1 = 990 - birth_year 

. gen age2 = 7 - birth_month

. gen age = age1 if age2 > 0 
(5944389 missing values generated)

. replace age = age1 - 1 if age2 <= 0 
(5944389 real changes made)

. drop age1 age2 

. drop if age <0 | age > 120 
(0 observations deleted)

. 
. ren houstype hktype

. 
. * have children at home 
. gen child = relation == 3 

. egen child_num = sum(child), by(hhid)

. tab child_num

  child_num |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |  1,180,736       10.30       10.30
          1 |  2,334,406       20.36       30.66
          2 |  3,698,116       32.26       62.92
          3 |  2,383,727       20.79       83.71
          4 |  1,150,931       10.04       93.75
          5 |    463,472        4.04       97.79
          6 |    171,838        1.50       99.29
          7 |     55,412        0.48       99.78
          8 |     17,867        0.16       99.93
          9 |      5,326        0.05       99.98
         10 |      1,738        0.02       99.99
         11 |        522        0.00      100.00
         12 |        196        0.00      100.00
         13 |         64        0.00      100.00
         14 |         40        0.00      100.00
------------+-----------------------------------
      Total | 11,464,391      100.00

. drop if child_num == 0
(1180736 observations deleted)

. 
. gen boy = child & sex == 1 

. gen girl = child & sex == 2

. egen num_boy = sum(boy), by(hhid)

. egen num_girl = sum(girl), by(hhid)

. 
. * at least mother information 
. gen father = (relation == 1 | relation == 2) & sex == 1

. gen mother = (relation == 2 | relation == 1 ) & sex == 2 

. egen mother_num = sum(mother) ,by(hhid)

. tab mother_num

 mother_num |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |    408,852        3.98        3.98
          1 |  9,874,803       96.02      100.00
------------+-----------------------------------
      Total | 10,283,655      100.00

. drop if mother_num != 1 
(408852 observations deleted)

. 
. 
. * Mother age, child age, birth age 
. gen f_age = age if father 
(7842986 missing values generated)

. gen m_age = age if mother 
(7633638 missing values generated)

. egen h_f_age = max(f_age), by(hhid)
(736232 missing values generated)

. egen h_m_age = max(m_age), by(hhid)

. gen c_age = age if child 
(5026974 missing values generated)

. egen h_c_age = max(c_age), by(hhid)

. drop if h_m_age - h_c_age <= 15
(54451 observations deleted)

. drop if h_m_age - h_c_age > 50
(2589 observations deleted)

. gen m_birth_age = h_m_age - h_c_age

. drop f_age m_age c_age

. 
. * born = survive (male, female)
. gen n_male = numbirm if mother 
(7586762 missing values generated)

. gen n_female = numbirf if mother 
(7586762 missing values generated)

. gen n_male_s = numsurm if mother 
(7586762 missing values generated)

. gen n_female_s = numsurf if mother 
(7586762 missing values generated)

. egen h_n_male = max(n_male), by(hhid)

. egen h_n_female = max(n_female), by(hhid)

. egen h_n_male_s = max(n_male_s), by(hhid)

. egen h_n_female_s = max(n_female_s), by(hhid)

. drop if h_n_male != h_n_male_s
(780705 observations deleted)

. drop if h_n_female != h_n_female_s
(462505 observations deleted)

. drop if h_n_male != num_boy
(1748819 observations deleted)

. drop if h_n_female != num_girl
(1061703 observations deleted)

. drop n_male n_female n_male_s n_female_s

. 
. * child age <= 18 
. gen child_age = age if child 
(2974210 missing values generated)

. egen max_child_age = max(child_age), by(hhid)

. drop if max_child_age >= 18
(991291 observations deleted)

. drop max_child_age 

. 
. 
. * father education, mother education
. recode edulevel (1 =1 )(2 = 2) (3 = 3) (4/10 = 4)
(edulevel: 97691 changes made)

. gen f_edu = edulevel if father
(3658724 missing values generated)

. gen m_edu = edulevel if mother 
(3585039 missing values generated)

. egen h_f_edu = max(f_edu), by(hhid)
(216441 missing values generated)

. egen h_m_edu = max(m_edu), by(hhid)

. 
. * father eth, mother eth
. gen f_han = nation == 1 if father
(3658724 missing values generated)

. gen m_han = nation == 1 if mother 
(3585039 missing values generated)

. egen h_f_han = max(f_han), by(hhid)
(216441 missing values generated)

. egen h_m_han = max(m_han), by(hhid)

. gen h_fm_min = h_f_han == 0 | h_f_han == 0 

. 
. * keep child data 
. keep if child 
(2558855 observations deleted)

. keep hhid prov sex age hktype birth_year birth_ym edulevel h_* child_num m_birth_age resid_type birth_month urban_hukou

. sort hhid age 

. 
. gen twins = hhid == hhid[_n-1] & age == age[_n-1] & birth_year == birth_year[_n-1] & birth_month == birth_month[_n-1]

. replace twins = hhid == hhid[_n+1] & age == age[_n+1] & birth_year == birth_year[_n+1] & birth_month == birth_month[_n+1]
>  if twins == 0
(11727 real changes made)

. 
. 
. preserve 

. keep hhid birth_year birth_month age

. duplicates drop 

Duplicates in terms of all variables

(11745 observations deleted)

. gsort hhid birth_year birth_month -age

. bys hhid: gen order = _n 

. save "order90",replace
file order90.dta saved

. restore

. 
. merge m:1 hhid age birth_year birth_month using "order90"

    Result                           # of obs.
    -----------------------------------------
    not matched                             0
    matched                         2,213,885  (_merge==3)
    -----------------------------------------

. drop _merge 

. gen year = 1990 

. count
2213885

. save "twins1990",replace 
file twins1990.dta saved

. cap erase "order90.dta"

. 
. **************
. 
. use "$raw_path/census2000",clear 

. de

Contains data from /Users/Wei/Dropbox/Census/census2000.dta
  obs:    11,804,344                          
 vars:            94                          17 Feb 2014 19:58
 size: 1,416,521,280                          
---------------------------------------------------------------------------------------------------------------------------
              storage   display    value
variable name   type    format     label      variable label
---------------------------------------------------------------------------------------------------------------------------
h0              byte    %10.0g                h0
id              str18   %18s                  id
h02             byte    %10.0g                h02
h031            byte    %10.0g                h031
h032            byte    %10.0g                h032
h041            byte    %10.0g                h041
h042            byte    %10.0g                h042
h051            byte    %10.0g                h051
h052            byte    %10.0g                h052
h061            byte    %10.0g                h061
h062            byte    %10.0g                h062
h071            byte    %10.0g                h071
h072            byte    %10.0g                h072
h081            byte    %10.0g                h081
h082            byte    %10.0g                h082
h09             byte    %10.0g                h09
h10             int     %10.0g                h10
h11             byte    %10.0g                h11
h12             byte    %10.0g                h12
h13             int     %10.0g                h13
h14             byte    %10.0g                h14
h15             byte    %10.0g                h15
h16             byte    %10.0g                h16
h17             byte    %10.0g                h17
h18             byte    %10.0g                h18
h19             byte    %10.0g                h19
h20             byte    %10.0g                h20
h21             byte    %10.0g                h21
h22             byte    %10.0g                h22
h23             byte    %10.0g                h23
ha0             byte    %10.0g                ha0
ha1             byte    %10.0g                ha1
ha2             byte    %10.0g                ha2
ha3             byte    %10.0g                ha3
ha4             byte    %10.0g                ha4
ha5             byte    %10.0g                ha5
ha6             byte    %10.0g                ha6
ha7             byte    %10.0g                ha7
ha8             byte    %10.0g                ha8
ha9             byte    %10.0g                ha9
ha10            int     %10.0g                ha10
ha11            byte    %10.0g                ha11
ha20            byte    %10.0g                ha20
r0              byte    %10.0g                r0
r01             byte    %10.0g                r01
r02             byte    %10.0g                r02
r03             byte    %10.0g                r03
r041            int     %10.0g                r041
r042            byte    %10.0g                r042
r05             byte    %10.0g                r05
r061            byte    %10.0g                r061
r062            byte    %10.0g                r062
r063            byte    %10.0g                r063
r07             byte    %10.0g                r07
r081            byte    %10.0g                r081
r082            byte    %10.0g                r082
r09             byte    %10.0g                r09
r101            byte    %10.0g                r101
r102            byte    %10.0g                r102
r103            byte    %10.0g                r103
r104            byte    %10.0g                r104
r11             byte    %10.0g                r11
r12             byte    %10.0g                r12
r131            byte    %10.0g                r131
r132            byte    %10.0g                r132
r14             byte    %10.0g                r14
r151            byte    %10.0g                r151
r152            byte    %10.0g                r152
r16             byte    %10.0g                r16
r17             byte    %10.0g                r17
r18             byte    %10.0g                r18
r19             int     %10.0g                r19
r20             int     %10.0g                r20
r211            byte    %10.0g                r211
r212            int     %10.0g                r212
r22             byte    %10.0g                r22
r23             byte    %10.0g                r23
r241            int     %10.0g                r241
r242            byte    %10.0g                r242
r251            byte    %10.0g                r251
r252            byte    %10.0g                r252
r253            byte    %10.0g                r253
r254            byte    %10.0g                r254
r261            byte    %10.0g                r261
r262            byte    %10.0g                r262
r263            byte    %10.0g                r263
r264            byte    %10.0g                r264
r265            byte    %10.0g                r265
ra0             byte    %10.0g                ra0
ra1             int     %10.0g                ra1
ra2             byte    %10.0g                ra2
ra20            byte    %10.0g                ra20
ra21            byte    %10.0g                ra21
ra22            byte    %10.0g                ra22
---------------------------------------------------------------------------------------------------------------------------
Sorted by:  

. 
. ren h02 hubie 

. ren r07 hktype 

. ren r041 birth_year 

. ren r042 birth_month 

. ren r02 relation 

. drop h0 hubie 

. ren r03 sex 

. ren r23 marr

. ren r241 marryy1st

. ren r242 marrym1st

. ren r251 numbirm

. ren r252 numbirf

. ren r253 numsurm

. ren r254 numsurf

. ren r151 schooling

. ren r05 nation

. ren ra0 resid_type

. gen prov = substr(id, 1,2)

. egen hhid = group(id)

. keep hhid  hktype birth_year birth_month sex relation marr marryy1st marrym1st numbir* numsur* schooling nation resid_typ
> e prov

. de

Contains data from /Users/Wei/Dropbox/Census/census2000.dta
  obs:    11,804,344                          
 vars:            17                          17 Feb 2014 19:58
 size:   271,499,912                          
---------------------------------------------------------------------------------------------------------------------------
              storage   display    value
variable name   type    format     label      variable label
---------------------------------------------------------------------------------------------------------------------------
relation        byte    %10.0g                r02
sex             byte    %10.0g                r03
birth_year      int     %10.0g                r041
birth_month     byte    %10.0g                r042
nation          byte    %10.0g                r05
hktype          byte    %10.0g                r07
schooling       byte    %10.0g                r151
marr            byte    %10.0g                r23
marryy1st       int     %10.0g                r241
marrym1st       byte    %10.0g                r242
numbirm         byte    %10.0g                r251
numbirf         byte    %10.0g                r252
numsurm         byte    %10.0g                r253
numsurf         byte    %10.0g                r254
resid_type      byte    %10.0g                ra0
prov            str2    %9s                   
hhid            float   %9.0g                 group(id)
---------------------------------------------------------------------------------------------------------------------------
Sorted by:  
     Note:  dataset has changed since last saved

. 
. gen age1 = 2000 - birth_year 

. gen age = age1 if birth_month< 11 
(1961020 missing values generated)

. replace age = age1 -1  if birth_month >= 11 
(1961020 real changes made)

. drop age1  

. 
. drop if age >= 120 
(0 observations deleted)

. drop if hktype == 0
(1734 observations deleted)

. 
. egen num_people= sum(1), by(hhid)

. drop if num_people > 3000
(454076 observations deleted)

. drop num_people

. * have children at home 
. gen child = relation == 2 

. egen child_num = sum(child), by(hhid)

. drop if child_num == 0
(1806108 observations deleted)

. gen boy = child & sex == 1 

. gen girl = child & sex == 2

. egen num_boy = sum(boy), by(hhid)

. egen num_girl = sum(girl), by(hhid)

. 
. 
. * at least mother information 
. gen father = (relation == 1 | relation == 0) & sex == 1

. gen mother = (relation == 0 | relation == 1 ) & sex == 2 

. egen mother_num = sum(mother) ,by(hhid)

. tab mother_num

 mother_num |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |    362,041        3.79        3.79
          1 |  9,180,385       96.21      100.00
------------+-----------------------------------
      Total |  9,542,426      100.00

. drop if mother_num != 1 
(362041 observations deleted)

. 
. * Mother first marriage 
. gen m_first = marr == 2 & mother

. egen h_m_first = max(m_first),by(hhid)

. keep if h_m_first == 1 
(487745 observations deleted)

. 
. 
. gen m_marr_1 = marryy1st if mother 
(6516424 missing values generated)

. egen h_year_mar1 = max(m_marr_1), by(hhid)

. gen m_marr_1m = marrym1st if mother 
(6516424 missing values generated)

. egen h_month_mar1 = max(m_marr_1m), by(hhid)

. 
. 
. * Mother age, child age, birth age 
. gen f_age = age if father 
(6616562 missing values generated)

. gen m_age = age if mother 
(6516424 missing values generated)

. egen h_f_age = max(f_age), by(hhid)
(295190 missing values generated)

. egen h_m_age = max(m_age), by(hhid)

. gen c_age = age if child 
(5217202 missing values generated)

. egen h_c_age = max(c_age), by(hhid)

. drop if h_m_age - h_c_age <= 15
(17635 observations deleted)

. gen m_birth_age = h_m_age - h_c_age

. 
. 
. * born = survive (male, female)
. 
. gen n_male = numbirm if mother 
(6821870 missing values generated)

. gen n_female = numbirf if mother 
(6822010 missing values generated)

. gen n_male_s = numsurm if mother 
(6822825 missing values generated)

. gen n_female_s = numsurf if mother 
(6823015 missing values generated)

. egen h_n_male = max(n_male), by(hhid)
(1453461 missing values generated)

. egen h_n_female = max(n_female),by(hhid)
(1453972 missing values generated)

. egen h_n_male_s = max(n_male_s),by(hhid)
(1456742 missing values generated)

. egen h_n_female_s = max(n_female_s), by(hhid)
(1457382 missing values generated)

. drop if h_n_male != h_n_male_s
(130552 observations deleted)

. drop if h_n_female != h_n_female_s
(94510 observations deleted)

. drop if h_n_male != num_boy
(2024501 observations deleted)

. drop if h_n_female != num_girl
(636552 observations deleted)

. drop h_n_male h_n_male_s h_n_female h_n_female_s 

. 
. * child age < 18 
. gen child_age = age if child 
(3320812 missing values generated)

. egen max_child_age = max(child_age), by(hhid)

. drop if max_child_age >= 18
(1038896 observations deleted)

. 
. 
. * father education, mother education
. recode schooling (0/2 = 1) (3 =2)(4=3)(5/10 = 4)
(schooling: 4043182 changes made)

. gen f_edu = schooling if father
(3557449 missing values generated)

. gen m_edu = schooling if mother 
(3494090 missing values generated)

. egen h_f_edu = max(f_edu), by(hhid)
(177668 missing values generated)

. egen h_m_edu = max(m_edu), by(hhid)

. 
. * father eth, mother eth
. gen f_han = nation == 1 if father
(3557449 missing values generated)

. gen m_han = nation == 1 if mother 
(3494090 missing values generated)

. egen h_f_han = max(f_han), by(hhid)
(177668 missing values generated)

. egen h_m_han = max(m_han), by(hhid)

. gen h_fm_min = h_f_han == 0 | h_f_han == 0 

. gen urban_hukou = hktype == 2 

. 
. * keep child data 
. keep if child 
(2772853 observations deleted)

. keep hhid sex age hktype birth_year schooling h_year_mar1  h_month_mar1  h_* child_num m_birth_age prov resid_type birth_
> month urban_hukou

. 
. gsort hhid age -birth_year -birth_month

. drop if birth_year == . 
(0 observations deleted)

. drop if birth_month == . 
(0 observations deleted)

. gen twins = hhid == hhid[_n-1] & age == age[_n-1] & birth_year == birth_year[_n-1] & birth_month == birth_month[_n-1] 

. replace twins = hhid == hhid[_n+1] & age == age[_n+1] & birth_year == birth_year[_n+1] & birth_month == birth_month[_n+1]
>  if twins == 0
(14304 real changes made)

. 
. preserve 

. keep hhid birth_year birth_month age 

. duplicates drop 

Duplicates in terms of all variables

(14339 observations deleted)

. gsort hhid birth_year birth_month -age

. bys hhid: gen order = _n

. save "order00",replace
file order00.dta saved

. restore 

. 
. merge m:1 hhid age birth_year birth_month using "order00"

    Result                           # of obs.
    -----------------------------------------
    not matched                             0
    matched                         1,977,141  (_merge==3)
    -----------------------------------------

. drop _merge 

. gen year = 2000

. count
1977141

. save "twins2000",replace 
file twins2000.dta saved

. cap erase "order00.dta"

. 
. 
. * 2005 Population Sample 
. 
. use "$raw_path/pdata1_num_ren",clear

. de

Contains data from /Users/Wei/Dropbox/Census/pdata1_num_ren.dta
  obs:     2,585,481                          
 vars:            88                          6 Jul 2007 15:04
 size:   299,915,796                          
---------------------------------------------------------------------------------------------------------------------------
              storage   display    value
variable name   type    format     label      variable label
---------------------------------------------------------------------------------------------------------------------------
region          long    %10.0g                da_code:��������
hhid            long    %12.0g                id:�����
hhtype          byte    %10.0g                h2:����
n_hh            byte    %8.0g                 h3_01:������ס����
n_hk_hh         byte    %8.0g                 h3_02:�����ڱ�������
n_mbirth_hh     byte    %10.0g                h4_01:������������(��)
n_fbirth_hh     byte    %10.0g                h4_02:������������(Ů)
n_mdeath_hh     byte    %10.0g                h5_01:������������(��)
n_fdeath_hh     byte    %10.0g                h5_02:������������(Ů)
use_h           byte    %10.0g                h6:ס����;
nf_build        byte    %10.0g                h7:��������
m_build         byte    %10.0g                h8:����סլ�����ṹ
t_build         int     %10.0g                h9:����סլ����ʱ��
nroom_h         byte    %10.0g                h10:ס������
nsm_h           int     %10.0g                h11:ס���������
ifshare_h       byte    %10.0g                h12:��ס�����Ƿ���������ס��
ifwat_h         byte    %10.0g                h13:�Ƿ���������ˮ
ifkit_h         byte    %10.0g                h14:ס�������޳���
fuel_h          byte    %10.0g                h15:��Ҫ����ȼ��
iftoil_h        byte    %10.0g                h16:ס�������޲���
ifbath_h        byte    %10.0g                h17:ס��������ϴ����ʩ
how_h           byte    %10.0g                h18:ס����Դ
c1wan_h         int     %8.0g                 h19_01:��Ԫ������ס�����ã�
c2qian_h        byte    %8.0g                 h19_02:ǧԪ������ס�����ã�
rent_h          int     %10.0g                h20:���ⷿ����
name            byte    %10.0g                r1:����
relation        byte    %10.0g                r2:�뻧����ϵ
sex             byte    %10.0g                r3:�Ա�
year_birth      int     %10.0g                r4_02:��������_��
moth_birth      byte    %10.0g                r4_03:��������_��
ethnic          byte    %10.0g                r5:����
where_hk        byte    %10.0g                r6:���ڵǼǵ����
county_hk       byte    %10.0g                r6_01:���ڵǼ�_������
city_hk         byte    %10.0g                r6_02:���ڵǼ�_������
prov_hk         byte    %10.0g                r6_03:���ڵǼ�_����ʡ
where_res       byte    %10.0g                r7:����ʱ���ס��
county_res      str2    %2s                   r7_01:����ʱ���ס��_������
city_res        double  %10.0g                r7_02:����ʱ���ס��_������
prov_res        byte    %10.0g                r7_03:����ʱ���ס��_����ʡ
time_out        byte    %10.0g                r8:�뿪���ڵǼǵ�ʱ��
cause_out       byte    %10.0g                r9:�뿪���ڵǼǵ�ԭ��
hkptype         byte    %10.0g                r10:���ڵǼǵ�����
hktype          byte    %10.0g                r11:��������
nbroth          byte    %10.0g                r12_01:�ֵ�����
nsister         byte    %10.0g                r12_02:��������
health          byte    %10.0g                r13:���彡�����
where_1y_res    byte    %10.0g                r14:һ��ǰ��ס��
prov_1y_res     byte    %10.0g                r14_01:һ��ǰ��ס��_ʡ
where_5y_res    byte    %10.0g                r15:����ǰ��ס��
prov_5y_res     byte    %10.0g                r15_01:����ǰ��ס��_ʡ
literacy        byte    %10.0g                r16:�Ƿ�ʶ��
educ            byte    %10.0g                r17:�ܽ����̶�
ifend_educ      byte    %10.0g                r18:ѧҵ������
ifwork          byte    %10.0g                r19:���ܹ������
hour_w          byte    %10.0g                r19_01:���ܹ���ʱ��
ind             byte    %10.0g                r20_02:ҵ��Χ����ҵ��
occ             byte    %10.0g                r21:ְҵ
type_unit       byte    %10.0g                r22:���ܹ����ĵ�λ��������
status_w        byte    %10.0g                r23:��ҵ����
ifcont          byte    %10.0g                r24:ǩ���Ͷ���ͬ���
term_cont       byte    %10.0g                r24_01:�̶��ں�ͬ����
income          long    %12.0g                r25:�������
cause_nw        byte    %10.0g                r26:����δ����ԭ��
how_sjob        byte    %10.0g                r27:���������Ƿ��ҹ�����
ifready_job     byte    %10.0g                r28:�ܷ���
dur_nw          byte    %10.0g                r28_01:����δ����ʱ��
insu_unem       byte    %10.0g                r29_01:ʧҵ����
pension         byte    %10.0g                r29_02:���ϱ���
medicare        byte    %10.0g                r29_03:����ҽ�Ʊ���
source_liv      byte    %10.0g                r30:��Ҫ������Դ
maritus         byte    %10.0g                r31:����״��
year_mar1       int     %10.0g                r32_02:������
month_mar1      byte    %10.0g                r32_03:������
n_mbirth        byte    %10.0g                r33_01:������Ů��_��
n_fbirth        byte    %10.0g                r33_02:������Ů��_Ů
n_mchild        byte    %10.0g                r34_01:�����Ů��_��
n_fchild        byte    %10.0g                r34_02:�����Ů��_Ů
ifbirth         byte    %10.0g                r35:�������
month_b1        byte    %10.0g                r35_01:����ʱ��_��
sex_b1          byte    %10.0g                r35_02:����Ӥ���Ա�
month_b2        byte    %10.0g                r35_03:�����ڶ�����������ʱ��_��
sex_b2          byte    %10.0g                r35_04:�����ڶ������������Ա�
r99             byte    %10.0g                
age             int     %10.0g                age: computed by NBS
ave_age         int     %10.0g                
power_2         float   %9.0g                 power_2: weights computed by NBS
city_flag       str1    %1s                   city_flag: type of residence
reg_flag        str1    %1s                   reg_flag: A.local,B.migrant?
---------------------------------------------------------------------------------------------------------------------------
Sorted by:  

. 
. keep region hhid hhtype hktype sex ethnic year_birth moth_birth relation maritus year_mar1 month_mar1 educ age n_*birth n
> _*child city_flag

. de

Contains data from /Users/Wei/Dropbox/Census/pdata1_num_ren.dta
  obs:     2,585,481                          
 vars:            19                          6 Jul 2007 15:04
 size:    72,393,468                          
---------------------------------------------------------------------------------------------------------------------------
              storage   display    value
variable name   type    format     label      variable label
---------------------------------------------------------------------------------------------------------------------------
region          long    %10.0g                da_code:��������
hhid            long    %12.0g                id:�����
hhtype          byte    %10.0g                h2:����
relation        byte    %10.0g                r2:�뻧����ϵ
sex             byte    %10.0g                r3:�Ա�
year_birth      int     %10.0g                r4_02:��������_��
moth_birth      byte    %10.0g                r4_03:��������_��
ethnic          byte    %10.0g                r5:����
hktype          byte    %10.0g                r11:��������
educ            byte    %10.0g                r17:�ܽ����̶�
maritus         byte    %10.0g                r31:����״��
year_mar1       int     %10.0g                r32_02:������
month_mar1      byte    %10.0g                r32_03:������
n_mbirth        byte    %10.0g                r33_01:������Ů��_��
n_fbirth        byte    %10.0g                r33_02:������Ů��_Ů
n_mchild        byte    %10.0g                r34_01:�����Ů��_��
n_fchild        byte    %10.0g                r34_02:�����Ů��_Ů
age             int     %10.0g                age: computed by NBS
city_flag       str1    %1s                   city_flag: type of residence
---------------------------------------------------------------------------------------------------------------------------
Sorted by:  
     Note:  dataset has changed since last saved

. 
. keep if hhtype == 1 
(77410 observations deleted)

. drop hhtype 

. 
. gen urban_hukou = hktype == 2 

. gen age1 = 2005 - year_birth 

. gen age2 = 11- moth_birth 

. ren age age_nbs 

. gen age = age1 if age2 > 0
(406513 missing values generated)

. replace age = age1 -1 if age2 <= 0 
(406513 real changes made)

. drop age_nbs 

. 
. drop if age >= 120 
(0 observations deleted)

. 
. 
. * have children at home 
. gen child = relation == 2 

. egen child_num = sum(child), by(region hhid)

. drop if child_num == 0
(695517 observations deleted)

. gen boy = child & sex == 1 

. gen girl = child & sex == 2

. egen num_boy = sum(boy), by(region hhid)

. egen num_girl = sum(girl), by(region hhid)

. 
. * at least mother information 
. gen father = (relation == 1 | relation == 0) & sex == 1

. gen mother = (relation == 0 | relation == 1 ) & sex == 2 

. egen mother_num = sum(mother), by(region hhid)

. tab mother_num

 mother_num |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |    425,449       23.47       23.47
          1 |  1,387,105       76.53      100.00
------------+-----------------------------------
      Total |  1,812,554      100.00

. drop if mother_num != 1 
(425449 observations deleted)

. 
. 
. * Mother first marriage 
. gen m_first = maritus == 2 & mother

. egen h_m_first = max(m_first),by(region hhid)

. keep if h_m_first == 1 
(82954 observations deleted)

. drop h_m_first

. gen m_marr_1 = year_mar1 if mother 
(943179 missing values generated)

. egen h_year_mar1 = max(m_marr_1), by(region hhid)

. gen m_marr_1m = month_mar1 if mother 
(943179 missing values generated)

. egen h_month_mar1 = max(m_marr_1m), by(region hhid)

. 
. * Mother age, child age, birth age 
. gen f_age = age if father 
(1027588 missing values generated)

. gen m_age = age if mother 
(943179 missing values generated)

. egen h_f_age = max(f_age), by(region hhid)
(237409 missing values generated)

. egen h_m_age = max(m_age), by(region hhid)

. gen c_age = age if child 
(782891 missing values generated)

. egen h_c_age = max(c_age), by(region hhid)

. drop if h_m_age - h_c_age <= 15
(2290 observations deleted)

. drop if h_m_age - h_c_age > 50
(746 observations deleted)

. gen m_birth_age = h_m_age - h_c_age

. 
. * born = survive (male, female)
. gen n_male = n_mbirth if mother 
(950906 missing values generated)

. gen n_female = n_fbirth if mother 
(950906 missing values generated)

. gen n_male_s = n_mchild if mother 
(950906 missing values generated)

. gen n_female_s = n_fchild if mother 
(950906 missing values generated)

. egen h_n_male = max(n_male), by(region hhid)
(43549 missing values generated)

. egen h_n_female = max(n_female), by(region hhid)
(43549 missing values generated)

. egen h_n_male_s = max(n_male_s), by(region hhid)
(43549 missing values generated)

. egen h_n_female_s = max(n_female_s), by(region hhid)
(43549 missing values generated)

. drop if h_n_male != h_n_male_s
(20778 observations deleted)

. drop if h_n_female != h_n_female_s
(12962 observations deleted)

. drop if h_n_male != num_boy
(297328 observations deleted)

. drop if h_n_female != num_girl
(204432 observations deleted)

. drop h_n_male h_n_male_s h_n_female h_n_female_s 

. 
. * child age < 18 
. gen child_age = age if child 
(435371 missing values generated)

. egen max_child_age = max(child_age), by(region hhid)

. drop if max_child_age >= 18
(201223 observations deleted)

. 
. 
. * father education, mother education
. recode educ (4/10=4), gen(schooling)
(30974 differences between educ and schooling)

. gen f_edu = schooling if father
(439960 missing values generated)

. gen m_edu = schooling if mother 
(400632 missing values generated)

. egen h_f_edu = max(f_edu), by(region hhid)
(106177 missing values generated)

. egen h_m_edu = max(m_edu), by(region hhid)

. 
. * father eth, mother eth
. gen f_han = ethnic == 1 if father
(439960 missing values generated)

. gen m_han = ethnic == 1 if mother 
(400632 missing values generated)

. egen h_f_han = max(f_han), by(region hhid)
(106177 missing values generated)

. egen h_m_han = max(m_han), by(region hhid)

. gen h_fm_min = h_f_han == 0 | h_f_han == 0 

. 
. 
. * keep child data 
. keep if child 
(324063 observations deleted)

. tostring region hhid, replace 
region was long now str6
hhid was long now str6

. egen hhid1 = group(region hhid)

. gen prov = substr(region, 1,2)

. destring prov, replace 
prov has all characters numeric; replaced as byte

. drop region hhid 

. ren hhid1 hhid 

. ren city_flag resid_type

. gen birth_year = year_birth

. gen birth_month = moth_birth

. keep hhid sex age hktype birth_year birth_month schooling h_year_mar1  h_month_mar1  h_* child_num m_birth_age prov resid
> _type urban_hukou

. 
. gsort hhid age -birth_year

. gen twins = hhid == hhid[_n-1] & age == age[_n-1] & birth_year == birth_year[_n-1] & birth_month == birth_month[_n-1]

. replace twins = hhid == hhid[_n+1] & age == age[_n+1] & birth_year == birth_year[_n+1]& birth_month == birth_month[_n+1] 
> if twins == 0
(1557 real changes made)

. 
. preserve 

. keep hhid age birth_year birth_month

. duplicates drop 

Duplicates in terms of all variables

(1565 observations deleted)

. gsort hhid birth_year birth_month -age

. bys hhid: gen order = _n

. save "order05",replace
file order05.dta saved

. restore 

. 
. merge m:1 hhid age birth_year birth_month using "order05"

    Result                           # of obs.
    -----------------------------------------
    not matched                             0
    matched                           240,329  (_merge==3)
    -----------------------------------------

. drop _merge 

. gen year = 2005

. count
240329

. save "twins2005",replace 
file twins2005.dta saved

. cap erase "order05.dta"

. 
. 
. use "twins1982", clear 

. destring prov, replace 
prov has all characters numeric; replaced as byte

. append using  "twins1990"
(note: variable age was int, now float to accommodate using data's values)

. tostring prov, replace 
prov was byte now str2

. append using  "twins2000",force 

. tostring resid_type,replace 
resid_type was float now str1

. destring prov, replace 
prov has all characters numeric; replaced as byte

. append using  "twins2005"

. * education issue
. replace edulevel = . if edulevel == 0 
(1679727 real changes made, 1679727 to missing)

. replace edulevel = schooling if mi(edulevel)
(1666655 real changes made)

. ren edulevel educ 

. drop schooling

. replace twins = 0 if twins == . 
(0 real changes made)

.  
. * province issue
. replace birth_year = 1000 + birth_year if year == 1990
(2213885 real changes made)

. replace birth_year = 1982 - age if year == 1982
(1717413 real changes made)

. replace birth_month = birth_ym - int(birth_ym/100) * 100 if mi(birth_month)
(0 real changes made)

. destring prov, replace 
prov already numeric; no replace

. gen province = prov 

. 
. gen birthyear = birth_year - 1 

. merge m:1 province birthyear  using "fines", keepusing(fine)

    Result                           # of obs.
    -----------------------------------------
    not matched                     2,013,902
        from master                 2,013,900  (_merge==1)
        from using                          2  (_merge==2)

    matched                         4,134,868  (_merge==3)
    -----------------------------------------

. drop if _merge == 2 
(2 observations deleted)

. drop _merge  

. ren fine fine_1 

. 
. replace birthyear = birthyear - 1 
(6148768 real changes made)

. 
. merge m:1 province birthyear  using "fines", keepusing(fine)
(label provcnlbl already defined)

    Result                           # of obs.
    -----------------------------------------
    not matched                     2,250,143
        from master                 2,250,142  (_merge==1)
        from using                          1  (_merge==2)

    matched                         3,898,626  (_merge==3)
    -----------------------------------------

. drop if _merge == 2 
(1 observation deleted)

. drop _merge 

. ren fine fine_2

. 
. 
. replace birthyear = birthyear + 2 
(6148768 real changes made)

. merge m:1 province birthyear  using "fines", keepusing(fine)
(label provcnlbl already defined)

    Result                           # of obs.
    -----------------------------------------
    not matched                     1,768,040
        from master                 1,768,037  (_merge==1)
        from using                          3  (_merge==2)

    matched                         4,380,731  (_merge==3)
    -----------------------------------------

. drop if _merge == 2 
(3 observations deleted)

. drop _merge 

. drop birthyear 

. 
. * Combine the provinces 
. drop if prov == 54 // Tibet 
(5927 observations deleted)

. replace prov = 44 if prov == 46 // Hainan 
(30976 real changes made)

. replace prov = 51 if prov == 50  // Chongqing
(40231 real changes made)

. 
. * Resident area type 
. destring resid_type, replace 
resid_type has all characters numeric; replaced as byte
(1717413 missing values generated)

. replace rural = resid_type == 3 if mi(rural)
(4425428 real changes made)

. 
. drop birth_ym

. drop h_c_age-h_m_first 

. destring prov, replace 
prov already numeric; no replace

. 
. 
. compress 
  age was float now byte
  child_num was float now byte
  h_f_age was float now byte
  h_m_age was float now byte
  m_birth_age was float now byte
  h_f_edu was float now byte
  h_m_edu was float now byte
  h_f_han was float now byte
  h_m_han was float now byte
  h_fm_min was float now byte
  twins was float now byte
  order was float now byte
  year was float now int
  urban_hukou was float now byte
  birth_year was float now int
  birth_month was float now byte
  h_year_mar1 was float now int
  h_month_mar1 was float now byte
  province was float now byte
  (331,713,414 bytes saved)

. gen male = sex == 1 

. gen urban = 1 - rural

. gen fineXhan = fine_1* (1-h_fm_min)
(2013261 missing values generated)

. gen h_fm_han = 1 - h_fm_min

. 
. sort year hhid 

. 
. gen twinsXorder = twins * order 

. replace twinsXorder = . if twinsXorder == 0 
(6073099 real changes made, 6073099 to missing)

. 
. gen birth1 = birth_year if order == 1 
(2783063 missing values generated)

. gen birth2 = birth_year if order == 2
(4275905 missing values generated)

. egen h_birth1 = max(birth1), by(hhid year) 

. egen h_birth2 = max(birth2), by(hhid year)
(1500370 missing values generated)

. gen time_y1 = h_birth1 - h_year_mar1 
(3929338 missing values generated)

. gen time_y2 = h_birth2 - h_birth1 
(1500370 missing values generated)

. drop birth1 birth2 h_birth1 h_birth2 

. 
. gen birth1 = birth_month if order == 1 
(3524085 missing values generated)

. gen birth2 = birth_month if order == 2
(4812881 missing values generated)

. egen h_birth1 = max(birth1), by(hhid year) 
(1717413 missing values generated)

. egen h_birth2 = max(birth2), by(hhid year)
(3012820 missing values generated)

. gen time_m1 = h_birth1 - h_month_mar1 
(3929338 missing values generated)

. gen time_m2 = h_birth2 - h_birth1 
(3012820 missing values generated)

. drop birth1 birth2 h_birth1 h_birth2 

. 
. gen time_1 = time_y1 * 12 + time_m1
(3929338 missing values generated)

. gen time_2 = time_y2 * 12 + time_m2
(3012820 missing values generated)

. count
6142841

. save "raw_data",replace 
file raw_data.dta saved

. cap erase "twins1982.dta"

. cap erase "twins1990.dta"

. cap erase "twins2000.dta"

. cap erase "twins2005.dta"

. 
. 
. ********** Table 1 & Table 2 ******
. 
. use "raw_data",clear

. keep hhid sex prov age rural urban child_num m_birth_age h_m_edu h_fm_min h_fm_han twins order year birth_year birth_mont
> h h_year_mar1 h_month_mar1 *_1 urban_hukou educ fine*

. 
. replace sex =. if twins == 1 
(69742 real changes made, 69742 to missing)

. drop educ 

. duplicates drop

Duplicates in terms of all variables

(34816 observations deleted)

. *br if (hhid == hhid[_n-1] & order == order[_n-1]) |(hhid == hhid[_n+1] & order == order[_n+1]) 
. replace urban_hukou = 1 if (hhid == hhid[_n-1] & order == order[_n-1]) |(hhid == hhid[_n+1] & order == order[_n+1]) 
(84 real changes made)

. duplicates drop 

Duplicates in terms of all variables

(78 observations deleted)

. drop if (hhid == hhid[_n-1] & order == order[_n-1]) |(hhid == hhid[_n+1] & order == order[_n+1]) 
(6 observations deleted)

. 
. replace fine = 0 if mi(fine) & birth_year <= 1979
(1715097 real changes made)

. replace fine_1 = 0 if mi(fine_1) & birth_year <= 1980 
(1970877 real changes made)

. replace fine_2 = 0 if mi(fine_2) & birth_year <= 1981 
(2215786 real changes made)

. 
. gen fine_e = 6*fine_1 + 6*fine_2 if year == 1982 
(4397811 missing values generated)

. replace fine_e = 3*fine_1 + 9*fine_2 if birth_month == 1 
(349243 real changes made)

. replace fine_e = 4*fine_1 + 8*fine_2 if birth_month == 2
(361648 real changes made)

. replace fine_e = 5*fine_1 + 7*fine_2 if birth_month == 3 
(345853 real changes made)

. replace fine_e = 6*fine_1 + 6*fine_2 if birth_month == 4
(317844 real changes made)

. replace fine_e = 7*fine_1 + 5*fine_2 if birth_month == 5 
(315947 real changes made)

. replace fine_e = 8*fine_1 + 4*fine_2 if birth_month == 6 
(325466 real changes made)

. replace fine_e = 9*fine_1 + 3*fine_2 if birth_month == 7 
(326104 real changes made)

. replace fine_e = 10*fine_1 + 2*fine_2 if birth_month == 8 
(362841 real changes made)

. replace fine_e = 11*fine_1 + 1*fine_2 if birth_month == 9
(387449 real changes made)

. replace fine_e = 12*fine_1  if birth_month == 10
(476869 real changes made)

. replace fine_e = 1*fine+11*fine_1  if birth_month == 11
(409852 real changes made)

. replace fine_e = 2*fine+10*fine_1  if birth_month == 12
(382616 real changes made)

. 
. replace fine_e = fine_e/12
(4123996 real changes made)

. 
. gen male = sex == 1 if !mi(sex)
(34852 missing values generated)

. 
. recode order (3/. = 3)
(order: 250778 changes made)

. 
. replace fine_1 = 0 if birth_year <= 1979
(0 real changes made)

. replace fine_2 = 0 if birth_year <= 1980
(0 real changes made)

. 
. forvalues i=1(1)3{
  2. gen order`i'Xfine = (order ==`i')*fine_1
  3. gen order`i'Xfine_e = (order ==`i')*fine_e
  4. 
. }
(34387 missing values generated)
(36079 missing values generated)
(34387 missing values generated)
(36079 missing values generated)
(34387 missing values generated)
(36079 missing values generated)

. 
. recode child_num (3/. = 3)
(child_num: 842479 changes made)

. 
. gen fine_eXmaj = fine_e * h_fm_han
(36079 missing values generated)

. gen fine_eXmin = fine_e * (1 - h_fm_han)
(36079 missing values generated)

. gen policy_79 = birth_year >= 1980

. gen policyXmaj = policy_79 * h_fm_han

. gen policyXmin = policy_79 * (1-h_fm_han)

. 
. replace twins = twins*100 
(34852 real changes made)

. 
. gen weight = 1

. replace weight = 1/0.2 if year == 2005
(237548 real changes made)

. 
. tab prov, gen(prov_)

       prov |      Freq.     Percent        Cum.
------------+-----------------------------------
         11 |     43,159        0.71        0.71
         12 |     49,441        0.81        1.52
         13 |    355,773        5.82        7.34
         14 |    180,078        2.95       10.29
         15 |    128,420        2.10       12.39
         21 |    205,253        3.36       15.75
         22 |    139,475        2.28       18.04
         23 |    202,233        3.31       21.35
         31 |     47,033        0.77       22.12
         32 |    329,260        5.39       27.51
         33 |    212,221        3.47       30.98
         34 |    314,351        5.15       36.13
         35 |    166,920        2.73       38.86
         36 |    195,123        3.19       42.06
         37 |    471,661        7.72       49.78
         41 |    487,011        7.97       57.75
         42 |    292,744        4.79       62.54
         43 |    319,660        5.23       67.78
         44 |    420,806        6.89       74.67
         45 |    239,775        3.93       78.59
         51 |    472,816        7.74       86.33
         52 |    175,037        2.87       89.20
         53 |    212,396        3.48       92.68
         61 |    189,498        3.10       95.78
         62 |    135,765        2.22       98.00
         63 |     24,367        0.40       98.40
         64 |     30,962        0.51       98.91
         65 |     66,703        1.09      100.00
------------+-----------------------------------
      Total |  6,107,941      100.00

. forvalues i = 1(1)28 {
  2. gen prov`i'Xyob = (prov_`i' == 1 ) * (birth_year-1964)
  3. }

. drop prov_*

. drop prov1Xyob

. 
. gen cluster_id = prov  // province clusters

. replace urban_hukou = 8 if mi(urban_hukou)
(1710130 real changes made)

. 
. tab h_m_edu, gen(m_edu_)

    h_m_edu |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |  1,381,984       22.63       22.63
          2 |  2,403,691       39.35       61.98
          3 |  1,726,507       28.27       90.25
          4 |    595,759        9.75      100.00
------------+-----------------------------------
      Total |  6,107,941      100.00

. egen cell = group(year birth_year)

. count
6107941

. save "twins_order_data_reg", replace 
file twins_order_data_reg.dta saved

.  
. 
. ************* Time Data **********
. use "raw_data",clear

. replace fine = 0 if mi(fine) & birth_year <= 1979 
(1721682 real changes made)

. replace fine_1 = 0 if mi(fine_1) & birth_year <= 1980 
(1978611 real changes made)

. replace fine_2 = 0 if mi(fine_2) & birth_year <= 1981 
(2224700 real changes made)

. 
. gen fine_e = 6*fine_1 + 6*fine_2 if year == 1982 
(4425428 missing values generated)

. replace fine_e = 3*fine_1 + 9*fine_2 if birth_month == 1 
(351320 real changes made)

. replace fine_e = 4*fine_1 + 8*fine_2 if birth_month == 2
(363900 real changes made)

. replace fine_e = 5*fine_1 + 7*fine_2 if birth_month == 3 
(348073 real changes made)

. replace fine_e = 6*fine_1 + 6*fine_2 if birth_month == 4
(319889 real changes made)

. replace fine_e = 7*fine_1 + 5*fine_2 if birth_month == 5 
(318081 real changes made)

. replace fine_e = 8*fine_1 + 4*fine_2 if birth_month == 6 
(327679 real changes made)

. replace fine_e = 9*fine_1 + 3*fine_2 if birth_month == 7 
(328270 real changes made)

. replace fine_e = 10*fine_1 + 2*fine_2 if birth_month == 8 
(365161 real changes made)

. replace fine_e = 11*fine_1 + 1*fine_2 if birth_month == 9
(389808 real changes made)

. replace fine_e = 12*fine_1  if birth_month == 10
(479765 real changes made)

. replace fine_e = 1*fine+11*fine_1  if birth_month == 11
(412233 real changes made)

. replace fine_e = 2*fine+10*fine_1  if birth_month == 12
(384889 real changes made)

. 
. replace fine_e = fine_e/12
(4150977 real changes made)

. keep hhid prov year order time* fine* birth_year h_m_edu h_fm_min h_fm_han m_birth_age twins rural 

. sort year hhid order 

. drop if order == order[_n-1] & hhid == hhid[_n-1]
(34915 observations deleted)

. replace time_1 = . if time_1 <=0 | time_1 >= 100
(104993 real changes made, 104993 to missing)

. replace time_2 = . if time_2 <=0 | time_2 >= 100
(79395 real changes made, 79395 to missing)

. gen policy_79 = birth_year >= 1980

. gen policyXmaj = policy_79 * h_fm_han

. gen policyXmin = policy_79 * (1-h_fm_han)

. 
. gen weight = 1

. replace weight = 1/0.2 if year == 2005
(237545 real changes made)

. egen cell = group(year birth_year)

. 
. 
. tab prov, gen(prov_)

       prov |      Freq.     Percent        Cum.
------------+-----------------------------------
         11 |     43,159        0.71        0.71
         12 |     49,441        0.81        1.52
         13 |    355,774        5.82        7.34
         14 |    180,078        2.95       10.29
         15 |    128,420        2.10       12.39
         21 |    205,253        3.36       15.75
         22 |    139,475        2.28       18.04
         23 |    202,233        3.31       21.35
         31 |     47,033        0.77       22.12
         32 |    329,257        5.39       27.51
         33 |    212,220        3.47       30.98
         34 |    314,350        5.15       36.13
         35 |    166,921        2.73       38.86
         36 |    195,121        3.19       42.06
         37 |    471,658        7.72       49.78
         41 |    487,010        7.97       57.75
         42 |    292,742        4.79       62.54
         43 |    319,660        5.23       67.78
         44 |    420,803        6.89       74.67
         45 |    239,775        3.93       78.59
         51 |    472,816        7.74       86.33
         52 |    175,037        2.87       89.20
         53 |    212,395        3.48       92.68
         61 |    189,498        3.10       95.78
         62 |    135,765        2.22       98.00
         63 |     24,367        0.40       98.40
         64 |     30,962        0.51       98.91
         65 |     66,703        1.09      100.00
------------+-----------------------------------
      Total |  6,107,926      100.00

. forvalues i = 1(1)28 {
  2. gen prov`i'Xyob = (prov_`i' == 1 ) * (birth_year-1964)
  3. }

. drop prov_*

. drop prov1Xyob

. gen cluster_id = prov // province clusters 

. count
6107926

. save "time_data_reg", replace 
file time_data_reg.dta saved

. 
. ***** Regressions ****
. set more off 

. use "twins_order_data_reg", clear

. drop if mi(fine_e)
(36079 observations deleted)

. replace birth_month = 0 if mi(birth_month)
(1710130 real changes made)

. 
. set more off 

. gen fine_exhan = fine_e* h_fm_han

. gen policyxhan = (birth_year >= 1980) * h_fm_han

. 
. /* Appendix Table 1 */
. su twins rural h_fm_han age  m_birth_age i.order [aw = weight]

    Variable |     Obs      Weight        Mean   Std. Dev.       Min        Max
-------------+-----------------------------------------------------------------
       twins | 6.1e+06     6877738    .5770938   7.574718          0        100
       rural | 6.1e+06     6877738    .7285174   .4447244          0          1
    h_fm_han | 6.1e+06     6877738    .9304556   .2543776          0          1
         age | 6.1e+06     6877738    8.049805   4.668753          0         17
 m_birth_age | 6.1e+06     6877738    23.24653   2.971609         16         50
             |
       order |
          2  | 6.1e+06     6877738    .2962775   .4566149          0          1
          3  | 6.1e+06     6877738     .138293   .3452073          0          1

. su twins rural h_fm_han age  m_birth_age i.order if h_fm_han == 1 [aw = weight] 

    Variable |     Obs      Weight        Mean   Std. Dev.       Min        Max
-------------+-----------------------------------------------------------------
       twins | 5.7e+06     6399430    .5878805   7.644767          0        100
       rural | 5.7e+06     6399430     .722652   .4476898          0          1
    h_fm_han | 5.7e+06     6399430           1          0          1          1
         age | 5.7e+06     6399430    8.081194   4.670845          0         17
 m_birth_age | 5.7e+06     6399430    23.27883      2.953         16         50
             |
       order |
          2  | 5.7e+06     6399430    .2948117   .4559581          0          1
          3  | 5.7e+06     6399430    .1352666   .3420081          0          1

. su twins rural h_fm_han age  m_birth_age i.order if h_fm_han == 0 [aw = weight] 

    Variable |     Obs      Weight        Mean   Std. Dev.       Min        Max
-------------+-----------------------------------------------------------------
       twins |  417668      478308    .4327755   6.564325          0        100
       rural |  417668      478308    .8069926   .3946593          0          1
    h_fm_han |  417668      478308           0          0          0          0
         age |  417668      478308    7.629837   4.620209          0         17
 m_birth_age |  417668      478308    22.81437   3.178809         16         50
             |
       order |
          2  |  417668      478308    .3158885   .4648693          0          1
          3  |  417668      478308    .1787844   .3831721          0          1

. 
. gl control_1 = "rural h_fm_han i.h_m_edu i.order i.m_birth_age i.birth_month i.prov i.cell prov*Xyob"

. 
. /* Table 1 */
. reg twins fine_e $control_1 [aw = weight], cluster(cluster_id)
(sum of wgt is   6.8777e+06)
note: 71.cell omitted because of collinearity

Linear regression                                      Number of obs = 6071862
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.0011
                                                       Root MSE      =  7.5708

                            (Std. Err. adjusted for 28 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
       twins |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      fine_e |    .066357   .0383854     1.73   0.095    -.0124033    .1451173
       rural |  -.0616492   .0152299    -4.05   0.000    -.0928984      -.0304
    h_fm_han |   .1031398   .0234605     4.40   0.000     .0550029    .1512767
             |
     h_m_edu |
          2  |   .0479406   .0120148     3.99   0.000     .0232883    .0725929
          3  |   .0706034   .0197788     3.57   0.001     .0300207    .1111861
          4  |   .0410606   .0192903     2.13   0.043     .0014802    .0806411
             |
       order |
          2  |   .2194648   .0343272     6.39   0.000     .1490311    .2898985
          3  |   .1996223   .0224244     8.90   0.000     .1536113    .2456332
             |
 m_birth_age |
         17  |   .0249273    .073528     0.34   0.737    -.1259396    .1757943
         18  |   .0642405    .058745     1.09   0.284    -.0562944    .1847753
         19  |   .0532554   .0665982     0.80   0.431    -.0833929    .1899036
         20  |   .0767002   .0641468     1.20   0.242    -.0549182    .2083186
         21  |   .1079195   .0601643     1.79   0.084    -.0155275    .2313664
         22  |   .1478456   .0586493     2.52   0.018     .0275071     .268184
         23  |   .1864164   .0552058     3.38   0.002     .0731434    .2996895
         24  |   .1941372    .060662     3.20   0.003     .0696691    .3186053
         25  |    .226541    .057495     3.94   0.001      .108571    .3445111
         26  |   .2737557   .0566262     4.83   0.000     .1575684    .3899431
         27  |   .2939741   .0527658     5.57   0.000     .1857075    .4022406
         28  |   .3263292   .0681424     4.79   0.000     .1865126    .4661458
         29  |   .3482803   .0583918     5.96   0.000     .2284702    .4680904
         30  |   .3316377    .069979     4.74   0.000     .1880526    .4752227
         31  |   .4949118   .0891534     5.55   0.000     .3119842    .6778395
         32  |   .3704612   .0887883     4.17   0.000     .1882827    .5526397
         33  |   .3295932   .0931623     3.54   0.001       .13844    .5207464
         34  |   .4772959    .142996     3.34   0.002     .1838924    .7706994
         35  |   .6785839   .1889456     3.59   0.001     .2908996    1.066268
         36  |   .2310811   .1380802     1.67   0.106     -.052236    .5143982
         37  |   .2862968   .2855792     1.00   0.325    -.2996633    .8722569
         38  |   .3978362   .2208538     1.80   0.083    -.0553184    .8509907
         39  |   .0174309   .2058199     0.08   0.933    -.4048767    .4397385
         40  |   .7159921   .5158394     1.39   0.176    -.3424229    1.774407
         41  |   .5374998   .5095832     1.05   0.301    -.5080786    1.583078
         42  |   .4018518   .2904081     1.38   0.178    -.1940164      .99772
         43  |   .2654882   .3075828     0.86   0.396    -.3656196    .8965959
         44  |  -.0326223   .2537346    -0.13   0.899    -.5532427     .487998
         45  |   .0484224   .3245917     0.15   0.883    -.6175848    .7144296
         46  |  -.3445741   .0661785    -5.21   0.000    -.4803612    -.208787
         47  |   .4151059   .6125962     0.68   0.504    -.8418376    1.672049
         48  |  -.2999438   .0669323    -4.48   0.000    -.4372776   -.1626101
         49  |   .8941649   1.207763     0.74   0.465     -1.58396     3.37229
         50  |   -.213076   .0626737    -3.40   0.002    -.3416719   -.0844801
             |
 birth_month |
          1  |  -.6336984   .2793963    -2.27   0.032    -1.206972   -.0604246
          2  |  -.6282744   .2760585    -2.28   0.031      -1.1947   -.0618492
          3  |  -.5950054   .2726762    -2.18   0.038    -1.154491   -.0355202
          4  |  -.6027091   .2761537    -2.18   0.038     -1.16933   -.0360885
          5  |  -.5837521   .2799504    -2.09   0.047    -1.158163   -.0093414
          6  |  -.5594588   .2743371    -2.04   0.051    -1.122352    .0034344
          7  |  -.5810446   .2728798    -2.13   0.042    -1.140948   -.0211415
          8  |  -.5788869   .2716501    -2.13   0.042    -1.136267    -.021507
          9  |  -.5994413   .2799513    -2.14   0.041    -1.173854   -.0250286
         10  |   -.603979    .273741    -2.21   0.036    -1.165649   -.0423088
         11  |  -.6362061   .2738914    -2.32   0.028    -1.198185   -.0742273
         12  |  -.6116055   .2766081    -2.21   0.036    -1.179158   -.0440526
             |
        prov |
         12  |  -.1537491   .0958842    -1.60   0.120    -.3504873    .0429891
         13  |  -.2302941    .043911    -5.24   0.000    -.3203921   -.1401961
         14  |   -.311251   .0796541    -3.91   0.001    -.4746876   -.1478144
         15  |   .0246648    .066929     0.37   0.715    -.1126622    .1619918
         21  |  -.0635136   .0119089    -5.33   0.000    -.0879486   -.0390786
         22  |  -.1460981   .0880176    -1.66   0.109    -.3266953    .0344992
         23  |   .0058053   .0668194     0.09   0.931    -.1312967    .1429074
         31  |  -.0706258   .0393957    -1.79   0.084    -.1514591    .0102075
         32  |  -.2434168   .0364068    -6.69   0.000    -.3181175   -.1687162
         33  |  -.1718075   .0459271    -3.74   0.001     -.266042   -.0775729
         34  |  -.3090074   .0794222    -3.89   0.001    -.4719683   -.1460466
         35  |  -.1686537   .0363449    -4.64   0.000    -.2432273   -.0940801
         36  |  -.2952865   .0593961    -4.97   0.000    -.4171571   -.1734158
         37  |   -.164989   .0760588    -2.17   0.039    -.3210487   -.0089293
         41  |   -.287496    .056436    -5.09   0.000    -.4032932   -.1716988
         42  |   .0353642    .041899     0.84   0.406    -.0506054    .1213337
         43  |  -.2234777   .0457255    -4.89   0.000    -.3172987   -.1296567
         44  |  -.2622788   .0358405    -7.32   0.000    -.3358175     -.18874
         45  |  -.1507978   .0213778    -7.05   0.000    -.1946615   -.1069342
         51  |  -.3362621   .0592804    -5.67   0.000    -.4578954   -.2146288
         52  |  -.2642738   .0603753    -4.38   0.000    -.3881536    -.140394
         53  |  -.1741349   .0529067    -3.29   0.003    -.2826904   -.0655794
         61  |  -.3117486   .0617548    -5.05   0.000     -.438459   -.1850381
         62  |  -.3130495   .0669458    -4.68   0.000     -.450411    -.175688
         63  |   -.442645   .0787751    -5.62   0.000    -.6042781   -.2810119
         64  |  -.1485821   .0358411    -4.15   0.000    -.2221219   -.0750422
         65  |    -.08371    .029932    -2.80   0.009    -.1451255   -.0222946
             |
        cell |
          2  |  -.1064745   .0481406    -2.21   0.036    -.2052508   -.0076982
          3  |  -.2365571   .0434308    -5.45   0.000    -.3256698   -.1474443
          4  |  -.2105579   .0490385    -4.29   0.000    -.3111766   -.1099392
          5  |    -.18268   .0405582    -4.50   0.000    -.2658984   -.0994615
          6  |  -.1653554    .043785    -3.78   0.001    -.2551947    -.075516
          7  |  -.2344113   .0451805    -5.19   0.000    -.3271141   -.1417085
          8  |  -.2452562   .0492355    -4.98   0.000    -.3462791   -.1442333
          9  |  -.2602971   .0576437    -4.52   0.000    -.3785723   -.1420219
         10  |  -.2537017   .0607408    -4.18   0.000    -.3783316   -.1290718
         11  |  -.3166998   .0629673    -5.03   0.000    -.4458981   -.1875015
         12  |  -.2609291   .0576447    -4.53   0.000    -.3792063   -.1426519
         13  |  -.2903472   .0562752    -5.16   0.000    -.4058143   -.1748801
         14  |  -.2866947    .070441    -4.07   0.000    -.4312277   -.1421617
         15  |  -.2988542   .0729475    -4.10   0.000    -.4485302   -.1491783
         16  |  -.3316767   .0844179    -3.93   0.001     -.504888   -.1584654
         17  |  -.3720472   .1052525    -3.53   0.001    -.5880075   -.1560868
         18  |  -.3936557   .1090075    -3.61   0.001    -.6173205   -.1699908
         19  |   .4229194    .256202     1.65   0.110    -.1027637    .9486026
         20  |   .3534242   .2628217     1.34   0.190    -.1858414    .8926897
         21  |   .2982497   .2584915     1.15   0.259    -.2321311    .8286305
         22  |   .2425929   .2343178     1.04   0.310    -.2381876    .7233734
         23  |   .2598938   .2393223     1.09   0.287    -.2311551    .7509427
         24  |   .2264273   .2367894     0.96   0.347    -.2594243     .712279
         25  |   .2489314   .2291687     1.09   0.287    -.2212841    .7191468
         26  |   .2271665   .2312185     0.98   0.335    -.2472546    .7015877
         27  |   .2008169   .2098746     0.96   0.347    -.2298101     .631444
         28  |   .1814077   .1775242     1.02   0.316    -.1828419    .5456573
         29  |   .2144616   .1947228     1.10   0.280    -.1850765    .6139997
         30  |   .2064776   .1922681     1.07   0.292     -.188024    .6009791
         31  |   .2533448    .196592     1.29   0.208    -.1500286    .6567183
         32  |   .2689406   .1997597     1.35   0.189    -.1409324    .6788136
         33  |   .2836805   .2023057     1.40   0.172    -.1314164    .6987775
         34  |   .3002772    .198598     1.51   0.142    -.1072122    .7077666
         35  |   .3204827   .2042529     1.57   0.128    -.0986096    .7395749
         36  |   .2901507   .2016232     1.44   0.162    -.1235459    .7038472
         37  |   .3739907   .1912802     1.96   0.061    -.0184838    .7664652
         38  |   .1569158   .1995088     0.79   0.438    -.2524425     .566274
         39  |   .2527232   .2034601     1.24   0.225    -.1647424    .6701888
         40  |   .2852626   .1977731     1.44   0.161    -.1205343    .6910596
         41  |   .2743748   .2069661     1.33   0.196    -.1502845    .6990342
         42  |   .2848959   .2010767     1.42   0.168    -.1276795    .6974712
         43  |   .2822405   .1881829     1.50   0.145    -.1038789      .66836
         44  |   .3303612   .1934564     1.71   0.099    -.0665785    .7273009
         45  |   .3778523   .1955311     1.93   0.064    -.0233445     .779049
         46  |   .2960335   .1787547     1.66   0.109    -.0707408    .6628078
         47  |   .2904179   .1638742     1.77   0.088    -.0458243      .62666
         48  |    .293827   .1515881     1.94   0.063    -.0172061    .6048601
         49  |   .2901169   .1585501     1.83   0.078     -.035201    .6154347
         50  |   .2304062   .1320028     1.75   0.092    -.0404412    .5012535
         51  |   .1858877    .124016     1.50   0.146    -.0685722    .4403475
         52  |   .1886983   .1136571     1.66   0.108    -.0445069    .4219035
         53  |   .1743227   .1143481     1.52   0.139    -.0603002    .4089456
         54  |    .138946   .1078355     1.29   0.209    -.0823141    .3602062
         55  |   .1207309   .1153524     1.05   0.305    -.1159526    .3574144
         56  |   .1764998   .1221517     1.44   0.160    -.0741349    .4271345
         57  |   .1056992   .2447445     0.43   0.669    -.3964751    .6078735
         58  |   .2731043   .1790433     1.53   0.139    -.0942622    .6404709
         59  |   .2063213   .1830278     1.13   0.270    -.1692206    .5818633
         60  |   .2853329   .1944167     1.47   0.154    -.1135773     .684243
         61  |   .0977516   .1442229     0.68   0.504    -.1981694    .3936727
         62  |   .0853494   .1739605     0.49   0.628     -.271588    .4422869
         63  |   .1331129   .1403441     0.95   0.351    -.1548494    .4210751
         64  |   .0687056   .1552358     0.44   0.662    -.2498119    .3872231
         65  |   .1034251   .1351331     0.77   0.451    -.1738451    .3806953
         66  |   .0737357   .1670233     0.44   0.662    -.2689678    .4164393
         67  |   .0908602   .1352356     0.67   0.507    -.1866203    .3683408
         68  |   .1135793   .1374104     0.83   0.416    -.1683635    .3955221
         69  |  -.0293942   .1085884    -0.27   0.789    -.2521991    .1934107
         70  |   .0336252   .1239413     0.27   0.788    -.2206813    .2879317
         71  |          0  (omitted)
             |
   prov2Xyob |   .0106654   .0058549     1.82   0.080    -.0013478    .0226786
   prov3Xyob |   .0196656   .0024912     7.89   0.000     .0145541    .0247772
   prov4Xyob |   .0223638   .0049087     4.56   0.000     .0122921    .0324355
   prov5Xyob |   .0069773   .0041444     1.68   0.104    -.0015263     .015481
   prov6Xyob |   .0052547   .0005777     9.10   0.000     .0040693    .0064401
   prov7Xyob |   .0164978   .0058745     2.81   0.009     .0044442    .0285513
   prov8Xyob |   .0081773   .0042984     1.90   0.068    -.0006422    .0169968
   prov9Xyob |   .0056364   .0030762     1.83   0.078    -.0006755    .0119482
  prov10Xyob |   .0229419   .0022533    10.18   0.000     .0183185    .0275654
  prov11Xyob |    .010468   .0030241     3.46   0.002     .0042629     .016673
  prov12Xyob |   .0234786   .0055707     4.21   0.000     .0120485    .0349086
  prov13Xyob |   .0180147   .0022758     7.92   0.000      .013345    .0226843
  prov14Xyob |   .0138404   .0036547     3.79   0.001     .0063416    .0213392
  prov15Xyob |   .0253332   .0046616     5.43   0.000     .0157684     .034898
  prov16Xyob |   .0307459   .0035959     8.55   0.000     .0233677    .0381241
  prov17Xyob |    .001539   .0024903     0.62   0.542    -.0035707    .0066487
  prov18Xyob |    .009819   .0034408     2.85   0.008      .002759    .0168789
  prov19Xyob |   .0180172   .0019445     9.27   0.000     .0140275    .0220069
  prov20Xyob |   .0118561   .0011236    10.55   0.000     .0095506    .0141616
  prov21Xyob |   .0189417   .0040377     4.69   0.000      .010657    .0272264
  prov22Xyob |   .0157236   .0036062     4.36   0.000     .0083243    .0231228
  prov23Xyob |   .0067324    .003261     2.06   0.049     .0000414    .0134233
  prov24Xyob |   .0195013   .0041951     4.65   0.000     .0108937    .0281088
  prov25Xyob |   .0216408   .0039791     5.44   0.000     .0134763    .0298054
  prov26Xyob |   .0240551   .0050484     4.76   0.000     .0136967    .0344135
  prov27Xyob |    .010287   .0015045     6.84   0.000     .0072001    .0133739
  prov28Xyob |   .0111738   .0016223     6.89   0.000     .0078451    .0145025
       _cons |   .3485048   .0909587     3.83   0.001     .1618729    .5351367
------------------------------------------------------------------------------

. outreg2 using "table1_2.xls",replace keep(fine_e) dec(3)
table1_2.xls
dir : seeout

. reg twins fine_e $control_1 [aw = weight] if h_fm_han == 1, cluster(cluster_id)
(sum of wgt is   6.3994e+06)
note: h_fm_han omitted because of collinearity
note: 71.cell omitted because of collinearity

Linear regression                                      Number of obs = 5654194
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.0011
                                                       Root MSE      =  7.6407

                            (Std. Err. adjusted for 28 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
       twins |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      fine_e |    .071629   .0410504     1.74   0.092    -.0125994    .1558574
       rural |  -.0552251   .0162601    -3.40   0.002    -.0885882   -.0218621
    h_fm_han |          0  (omitted)
             |
     h_m_edu |
          2  |    .044863   .0126787     3.54   0.001     .0188484    .0708776
          3  |   .0668807   .0209857     3.19   0.004     .0238217    .1099397
          4  |   .0352226   .0196404     1.79   0.084    -.0050761    .0755213
             |
       order |
          2  |   .2262021   .0356322     6.35   0.000     .1530909    .2993133
          3  |      .2033   .0241952     8.40   0.000     .1536554    .2529445
             |
 m_birth_age |
         17  |   .0084564   .0920855     0.09   0.928    -.1804874    .1974002
         18  |   .0497653   .0742064     0.67   0.508    -.1024936    .2020242
         19  |    .030239   .0819132     0.37   0.715    -.1378329    .1983109
         20  |   .0610984     .07935     0.77   0.448    -.1017144    .2239112
         21  |   .0925782   .0759597     1.22   0.233    -.0632781    .2484346
         22  |    .135016   .0728893     1.85   0.075    -.0145404    .2845724
         23  |   .1702583   .0692082     2.46   0.021     .0282547    .3122618
         24  |   .1781895   .0759058     2.35   0.026     .0224436    .3339353
         25  |   .2174202   .0733293     2.96   0.006      .066961    .3678794
         26  |   .2644389   .0708967     3.73   0.001     .1189708    .4099069
         27  |   .2848048   .0684188     4.16   0.000      .144421    .4251887
         28  |    .310232   .0848131     3.66   0.001       .13621     .484254
         29  |   .3471095   .0690952     5.02   0.000     .2053378    .4888812
         30  |   .3174561   .0815042     3.89   0.001     .1502233     .484689
         31  |   .4992577   .1025295     4.87   0.000     .2888845    .7096309
         32  |    .379949   .1008336     3.77   0.001     .1730555    .5868425
         33  |    .330003   .1031739     3.20   0.004     .1183076    .5416985
         34  |   .5127524   .1569252     3.27   0.003     .1907684    .8347364
         35  |   .6980013   .2098818     3.33   0.003     .2673593    1.128643
         36  |   .2015918   .1418257     1.42   0.167    -.0894105    .4925941
         37  |   .3242661   .3189222     1.02   0.318    -.3301082    .9786404
         38  |   .3853239    .228635     1.69   0.103    -.0837965    .8544443
         39  |   .0227304   .2292549     0.10   0.922    -.4476618    .4931226
         40  |    .695046   .5508509     1.26   0.218    -.4352066    1.825299
         41  |   .0619495   .1709425     0.36   0.720    -.2887956    .4126946
         42  |   .4368459   .3199181     1.37   0.183    -.2195718    1.093264
         43  |   .1006813   .2885066     0.35   0.730    -.4912854    .6926479
         44  |  -.0338805   .2777848    -0.12   0.904    -.6038479    .5360869
         45  |   .0460058    .356846     0.13   0.898    -.6861817    .7781932
         46  |  -.3751167   .0738428    -5.08   0.000    -.5266295   -.2236039
         47  |  -.3237112     .07435    -4.35   0.000    -.4762648   -.1711576
         48  |  -.3348654   .0738601    -4.53   0.000    -.4864139    -.183317
         49  |   1.035187   1.370731     0.76   0.457    -1.777321    3.847696
         50  |  -.2352522    .072856    -3.23   0.003    -.3847404   -.0857641
             |
 birth_month |
          1  |  -.6752285   .2975287    -2.27   0.031    -1.285707     -.06475
          2  |  -.6730864   .2917684    -2.31   0.029    -1.271746    -.074427
          3  |  -.6431662   .2875337    -2.24   0.034    -1.233137   -.0531958
          4  |  -.6487868   .2915793    -2.23   0.035    -1.247058   -.0505154
          5  |  -.6296638   .2964927    -2.12   0.043    -1.238017    -.021311
          6  |  -.5958245     .29173    -2.04   0.051    -1.194405    .0027561
          7  |  -.6255651   .2894354    -2.16   0.040    -1.219437   -.0316928
          8  |   -.620396   .2871968    -2.16   0.040    -1.209675   -.0311169
          9  |  -.6423024   .2961086    -2.17   0.039    -1.249867   -.0347378
         10  |  -.6506456   .2890971    -2.25   0.033    -1.243824   -.0574673
         11  |  -.6757058   .2896059    -2.33   0.027    -1.269928   -.0814835
         12  |  -.6553033   .2916865    -2.25   0.033    -1.253795    -.056812
             |
        prov |
         12  |     -.1427   .1021857    -1.40   0.174    -.3523678    .0669678
         13  |  -.2489798   .0470473    -5.29   0.000     -.345513   -.1524467
         14  |  -.3070607   .0854416    -3.59   0.001    -.4823724   -.1317491
         15  |  -.0035259   .0707576    -0.05   0.961    -.1487086    .1416568
         21  |  -.0684188   .0137595    -4.97   0.000    -.0966511   -.0401866
         22  |  -.1432319   .0949426    -1.51   0.143     -.338038    .0515742
         23  |   .0062494   .0723568     0.09   0.932    -.1422144    .1547132
         31  |  -.0633453   .0418774    -1.51   0.142    -.1492705      .02258
         32  |  -.2372717   .0391553    -6.06   0.000    -.3176117   -.1569316
         33  |  -.1649539   .0495533    -3.33   0.003    -.2666289    -.063279
         34  |  -.3063569   .0852563    -3.59   0.001    -.4812883   -.1314254
         35  |  -.1661519   .0393246    -4.23   0.000    -.2468393   -.0854645
         36  |  -.2889234   .0639208    -4.52   0.000    -.4200779   -.1577688
         37  |  -.1600069   .0816451    -1.96   0.060    -.3275287     .007515
         41  |  -.2892744   .0606395    -4.77   0.000    -.4136965   -.1648524
         42  |   .0466004   .0451095     1.03   0.311    -.0459568    .1391575
         43  |  -.2319258   .0491652    -4.72   0.000    -.3328045   -.1310471
         44  |  -.2623994   .0376759    -6.96   0.000     -.339704   -.1850948
         45  |  -.1940048   .0213505    -9.09   0.000    -.2378124   -.1501973
         51  |  -.3458559   .0631422    -5.48   0.000    -.4754131   -.2162988
         52  |  -.3274429   .0629723    -5.20   0.000    -.4566513   -.1982345
         53  |  -.2218338   .0554933    -4.00   0.000    -.3356966    -.107971
         61  |  -.3078833   .0661794    -4.65   0.000    -.4436723   -.1720944
         62  |  -.2754159   .0715406    -3.85   0.001     -.422205   -.1286267
         63  |  -.4758814   .0828811    -5.74   0.000    -.6459394   -.3058235
         64  |  -.1360748   .0370938    -3.67   0.001    -.2121849   -.0599647
         65  |  -.1024192   .0335138    -3.06   0.005    -.1711838   -.0336546
             |
        cell |
          2  |  -.0978985   .0524399    -1.87   0.073    -.2054962    .0096992
          3  |  -.2367473   .0458166    -5.17   0.000    -.3307552   -.1427395
          4  |  -.2175333   .0543324    -4.00   0.000    -.3290141   -.1060525
          5  |   -.193775   .0445631    -4.35   0.000    -.2852109   -.1023392
          6  |  -.1740255   .0482097    -3.61   0.001    -.2729436   -.0751075
          7  |  -.2364157   .0476349    -4.96   0.000    -.3341544    -.138677
          8  |  -.2518138   .0531001    -4.74   0.000    -.3607663   -.1428614
          9  |   -.262106   .0608821    -4.31   0.000    -.3870258   -.1371862
         10  |  -.2643653   .0623745    -4.24   0.000    -.3923472   -.1363834
         11  |  -.3278991   .0656697    -4.99   0.000    -.4626423   -.1931559
         12  |  -.2675784   .0616708    -4.34   0.000    -.3941164   -.1410404
         13  |  -.3036754   .0639063    -4.75   0.000    -.4348004   -.1725505
         14  |  -.3070483   .0748144    -4.10   0.000    -.4605547   -.1535419
         15  |  -.3155336   .0760989    -4.15   0.000    -.4716757   -.1593916
         16  |  -.3494524    .088453    -3.95   0.001    -.5309429   -.1679619
         17  |  -.3990588   .1113537    -3.58   0.001    -.6275376     -.17058
         18  |  -.4151019   .1155997    -3.59   0.001    -.6522929   -.1779109
         19  |   .4832555   .2692584     1.79   0.084    -.0692172    1.035728
         20  |   .4033575   .2772998     1.45   0.157    -.1656148    .9723297
         21  |   .3423189   .2724001     1.26   0.220    -.2165999    .9012377
         22  |   .2813271   .2484261     1.13   0.267    -.2284012    .7910554
         23  |   .2927184   .2544893     1.15   0.260    -.2294504    .8148873
         24  |   .2596935   .2508306     1.04   0.310    -.2549683    .7743553
         25  |   .2846007   .2436885     1.17   0.253    -.2154068    .7846082
         26  |   .2616615   .2445474     1.07   0.294    -.2401084    .7634314
         27  |   .2338955   .2210233     1.06   0.299    -.2196068    .6873978
         28  |   .2062445   .1873689     1.10   0.281    -.1782048    .5906938
         29  |   .2429058   .2054098     1.18   0.247    -.1785602    .6643719
         30  |    .231144   .2017045     1.15   0.262    -.1827195    .6450075
         31  |   .2758197   .2074326     1.33   0.195    -.1497968    .7014362
         32  |   .2963869   .2104172     1.41   0.170    -.1353535    .7281274
         33  |   .3190609   .2133456     1.50   0.146     -.118688    .7568099
         34  |   .3322265   .2089736     1.59   0.124    -.0965518    .7610049
         35  |   .3534924   .2139274     1.65   0.110    -.0854504    .7924353
         36  |   .3202617   .2133021     1.50   0.145    -.1173981    .7579215
         37  |   .4069169   .2009129     2.03   0.053    -.0053223    .8191561
         38  |   .2003545   .2095994     0.96   0.348     -.229708     .630417
         39  |   .2837154   .2127468     1.33   0.193    -.1528051    .7202359
         40  |   .3185887   .2070786     1.54   0.136    -.1063014    .7434789
         41  |   .3114317   .2183178     1.43   0.165    -.1365194    .7593828
         42  |   .3119017   .2119945     1.47   0.153    -.1230751    .7468785
         43  |   .3074391   .1986253     1.55   0.133    -.1001064    .7149846
         44  |   .3643639   .2030373     1.79   0.084    -.0522342     .780962
         45  |   .4075254   .2052038     1.99   0.057     -.013518    .8285689
         46  |   .3321287   .1867765     1.78   0.087    -.0511051    .7153624
         47  |   .3217129   .1719975     1.87   0.072    -.0311967    .6746226
         48  |    .317359   .1570412     2.02   0.053    -.0048631     .639581
         49  |   .3158027   .1668526     1.89   0.069    -.0265505    .6581559
         50  |   .2619104   .1375844     1.90   0.068    -.0203895    .5442104
         51  |   .1971566   .1305801     1.51   0.143    -.0707717    .4650848
         52  |   .2073969   .1170051     1.77   0.088    -.0326777    .4474714
         53  |   .1956455   .1208124     1.62   0.117    -.0522412    .4435321
         54  |   .1521965   .1131865     1.34   0.190    -.0800431     .384436
         55  |   .1421173   .1199879     1.18   0.247    -.1040775    .3883122
         56  |   .1789138   .1288678     1.39   0.176    -.0855011    .4433287
         57  |   .1445866   .2565072     0.56   0.578    -.3817228     .670896
         58  |   .2623486   .1917618     1.37   0.183    -.1311141    .6558112
         59  |   .2279199   .1860819     1.22   0.231    -.1538886    .6097284
         60  |    .298562   .2060853     1.45   0.159    -.1242901    .7214142
         61  |   .0881761   .1492129     0.59   0.559    -.2179835    .3943358
         62  |   .1182457   .1843688     0.64   0.527    -.2600478    .4965393
         63  |   .1507235   .1499899     1.00   0.324    -.1570304    .4584773
         64  |   .0754062   .1677669     0.45   0.657    -.2688231    .4196355
         65  |   .1402616   .1385967     1.01   0.321    -.1441153    .4246384
         66  |   .0917787   .1769672     0.52   0.608     -.271328    .4548853
         67  |   .1172841   .1368195     0.86   0.399    -.1634463    .3980146
         68  |   .1195114   .1433798     0.83   0.412    -.1746795    .4137024
         69  |  -.0045385   .1108612    -0.04   0.968    -.2320068    .2229299
         70  |    .026121   .1323643     0.20   0.845    -.2454681    .2977101
         71  |          0  (omitted)
             |
   prov2Xyob |   .0114883   .0062348     1.84   0.076    -.0013045    .0242811
   prov3Xyob |   .0210032   .0026842     7.82   0.000     .0154958    .0265107
   prov4Xyob |   .0229558   .0052608     4.36   0.000     .0121614    .0337501
   prov5Xyob |   .0087655    .004401     1.99   0.057    -.0002646    .0177956
   prov6Xyob |   .0050742   .0006351     7.99   0.000     .0037711    .0063773
   prov7Xyob |   .0175635    .006327     2.78   0.010     .0045815    .0305455
   prov8Xyob |   .0091386    .004642     1.97   0.059    -.0003861    .0186633
   prov9Xyob |   .0063303   .0032731     1.93   0.064    -.0003855    .0130461
  prov10Xyob |   .0233398   .0024364     9.58   0.000     .0183408    .0283388
  prov11Xyob |   .0109342   .0032627     3.35   0.002     .0042397    .0176288
  prov12Xyob |    .024066    .005979     4.03   0.000     .0117982    .0363338
  prov13Xyob |   .0186328    .002459     7.58   0.000     .0135872    .0236783
  prov14Xyob |   .0142383   .0039308     3.62   0.001      .006173    .0223035
  prov15Xyob |   .0257862   .0050146     5.14   0.000     .0154971    .0360752
  prov16Xyob |    .031411   .0038793     8.10   0.000     .0234513    .0393706
  prov17Xyob |   .0017087   .0026802     0.64   0.529    -.0037907    .0072081
  prov18Xyob |   .0110213    .003708     2.97   0.006     .0034131    .0186294
  prov19Xyob |   .0186296   .0020474     9.10   0.000     .0144286    .0228305
  prov20Xyob |   .0154596   .0011798    13.10   0.000     .0130389    .0178803
  prov21Xyob |   .0202845   .0043151     4.70   0.000     .0114307    .0291384
  prov22Xyob |   .0210501   .0038204     5.51   0.000     .0132112    .0288889
  prov23Xyob |   .0090364   .0034695     2.60   0.015     .0019176    .0161552
  prov24Xyob |   .0201335   .0044936     4.48   0.000     .0109135    .0293536
  prov25Xyob |   .0202552    .004255     4.76   0.000     .0115247    .0289857
  prov26Xyob |   .0274241   .0053889     5.09   0.000     .0163671    .0384811
  prov27Xyob |   .0095815   .0016153     5.93   0.000     .0062671    .0128959
  prov28Xyob |   .0140802   .0018387     7.66   0.000     .0103076    .0178528
       _cons |   .4566365   .0989497     4.61   0.000     .2536085    .6596645
------------------------------------------------------------------------------

. outreg2 using "table1_2.xls", keep(fine_e) append dec(3)
table1_2.xls
dir : seeout

. reg twins fine_e $control_1 [aw = weight] if h_fm_han == 0, cluster(cluster_id)
(sum of wgt is   4.7831e+05)
note: h_fm_han omitted because of collinearity
note: 71.cell omitted because of collinearity

Linear regression                                      Number of obs =  417668
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.0014
                                                       Root MSE      =  6.5611

                            (Std. Err. adjusted for 28 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
       twins |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      fine_e |    .011366    .028837     0.39   0.697    -.0478025    .0705346
       rural |  -.1621174   .0434454    -3.73   0.001    -.2512599   -.0729749
    h_fm_han |          0  (omitted)
             |
     h_m_edu |
          2  |   .0761406   .0242294     3.14   0.004     .0264261    .1258551
          3  |    .103656   .0410114     2.53   0.018     .0195075    .1878044
          4  |   .1142308   .0785727     1.45   0.158     -.046987    .2754486
             |
       order |
          2  |   .1355769   .0280245     4.84   0.000     .0780754    .1930783
          3  |   .1545371   .0274543     5.63   0.000     .0982056    .2108686
             |
 m_birth_age |
         17  |   .0761727   .0658158     1.16   0.257    -.0588701    .2112155
         18  |   .1020507   .0792128     1.29   0.209    -.0604806     .264582
         19  |   .1650436   .0709721     2.33   0.028     .0194208    .3106664
         20  |   .1256938   .0511408     2.46   0.021     .0207616     .230626
         21  |   .1511241   .0535615     2.82   0.009     .0412251    .2610232
         22  |   .1585105   .0632284     2.51   0.018     .0287767    .2882444
         23  |   .2480329   .0482618     5.14   0.000     .1490078    .3470581
         24  |   .2647635   .0492796     5.37   0.000     .1636501     .365877
         25  |   .1940528   .0458579     4.23   0.000     .0999602    .2881453
         26  |   .2470362   .0549266     4.50   0.000     .1343363    .3597362
         27  |   .2729066   .0854709     3.19   0.004     .0975347    .4482784
         28  |   .4137225   .0843357     4.91   0.000     .2406799    .5867651
         29  |    .224525   .1221925     1.84   0.077    -.0261933    .4752433
         30  |   .3945662   .1588407     2.48   0.019      .068652    .7204803
         31  |   .3170655    .239937     1.32   0.197    -.1752445    .8093755
         32  |   .1315971   .1203363     1.09   0.284    -.1153125    .3785068
         33  |   .2208767   .1270375     1.74   0.093    -.0397826    .4815361
         34  |  -.0119938   .1876915    -0.06   0.950     -.397105    .3731175
         35  |   .3561839   .1738727     2.05   0.050    -.0005734    .7129413
         36  |    .429103   .2603319     1.65   0.111    -.1050539    .9632599
         37  |  -.2078218     .06485    -3.20   0.003    -.3408831   -.0747605
         38  |   .3829641   .5956532     0.64   0.526    -.8392154    1.605144
         39  |  -.1533771   .0562367    -2.73   0.011    -.2687653   -.0379888
         40  |   .7974732   .8632523     0.92   0.364    -.9737742    2.568721
         41  |   5.776812   5.193284     1.11   0.276    -4.878928    16.43255
         42  |  -.1417901   .0645775    -2.20   0.037    -.2742922   -.0092881
         43  |   1.459241   1.526043     0.96   0.347    -1.671941    4.590424
         44  |  -.1895381   .1001328    -1.89   0.069    -.3949938    .0159175
         45  |  -.0536314   .0597184    -0.90   0.377    -.1761635    .0689008
         46  |  -.1390777   .1283803    -1.08   0.288    -.4024923    .1243369
         47  |   7.566212   7.778862     0.97   0.339    -8.394694    23.52712
         48  |  -.2085807   .1283241    -1.63   0.116    -.4718801    .0547186
         49  |  -.1341594   .0694554    -1.93   0.064    -.2766701    .0083512
         50  |  -.0699098   .0604517    -1.16   0.258    -.1939464    .0541269
             |
 birth_month |
          1  |  -.2972646    .387828    -0.77   0.450    -1.093022    .4984926
          2  |  -.2540608   .3529165    -0.72   0.478    -.9781857     .470064
          3  |  -.1800478    .376596    -0.48   0.636    -.9527589    .5926634
          4  |  -.2099122    .367032    -0.57   0.572    -.9629998    .5431753
          5  |  -.1950249   .3831828    -0.51   0.615    -.9812512    .5912013
          6  |  -.2807004   .3740721    -0.75   0.460    -1.048233     .486832
          7  |  -.2064866   .3526175    -0.59   0.563    -.9299978    .5170247
          8  |  -.2440042   .3752469    -0.65   0.521    -1.013947    .5259388
          9  |  -.2506183   .3777519    -0.66   0.513    -1.025701    .5244647
         10  |  -.2061958   .3648867    -0.57   0.577    -.9548815    .5424899
         11  |  -.3375682   .3729275    -0.91   0.373    -1.102752    .4276159
         12  |  -.2528774   .3644524    -0.69   0.494    -1.000672    .4949172
             |
        prov |
         12  |  -1.016484   .0702911   -14.46   0.000     -1.16071   -.8722589
         13  |   .4927092   .0407099    12.10   0.000     .4091794     .576239
         14  |   .0182995   .0605996     0.30   0.765    -.1060407    .1426397
         15  |  -.0768196   .0577283    -1.33   0.194    -.1952682    .0416291
         21  |  -.2531983   .0290653    -8.71   0.000    -.3128354   -.1935612
         22  |  -.4605283   .0775049    -5.94   0.000    -.6195553   -.3015012
         23  |   -.226181   .0596624    -3.79   0.001    -.3485982   -.1037639
         31  |  -.8557064   .0682267   -12.54   0.000    -.9956959   -.7157168
         32  |  -.5479167   .0474324   -11.55   0.000    -.6452399   -.4505934
         33  |   -.241059   .0486885    -4.95   0.000    -.3409596   -.1411584
         34  |  -.7253567   .0643394   -11.27   0.000    -.8573702   -.5933431
         35  |  -.0281853   .0367482    -0.77   0.450    -.1035864    .0472159
         36  |   .0753857   .0679419     1.11   0.277    -.0640196     .214791
         37  |  -.9971552   .0600645   -16.60   0.000    -1.120397    -.873913
         41  |   .1714042   .0509246     3.37   0.002     .0669155    .2758928
         42  |  -.4028626   .0441852    -9.12   0.000    -.4935232    -.312202
         43  |  -.2328273   .0406253    -5.73   0.000    -.3161836   -.1494711
         44  |  -.0576751   .0455153    -1.27   0.216    -.1510648    .0357145
         45  |  -.4160427   .0353249   -11.78   0.000    -.4885234   -.3435621
         51  |   -.261865   .0614085    -4.26   0.000    -.3878649   -.1358651
         52  |  -.3801113   .0494909    -7.68   0.000    -.4816584   -.2785643
         53  |  -.3441012   .0443777    -7.75   0.000    -.4351566   -.2530457
         61  |  -.2285945   .0549849    -4.16   0.000    -.3414141   -.1157749
         62  |  -1.103853   .0532428   -20.73   0.000    -1.213098   -.9946079
         63  |  -.6568089   .0619038   -10.61   0.000     -.783825   -.5297928
         64  |  -.5020775   .0373494   -13.44   0.000    -.5787121   -.4254429
         65  |  -.4403671   .0353527   -12.46   0.000    -.5129049   -.3678292
             |
        cell |
          2  |  -.2828891   .2487823    -1.14   0.265    -.7933484    .2275701
          3  |  -.2732424   .2282265    -1.20   0.242    -.7415245    .1950396
          4  |   -.102865   .3485668    -0.30   0.770     -.818065    .6123349
          5  |   .0066876   .2888068     0.02   0.982    -.5858949    .5992702
          6  |  -.0513353   .2814364    -0.18   0.857    -.6287951    .5261245
          7  |  -.2716601   .2256854    -1.20   0.239    -.7347283     .191408
          8  |  -.2026106   .2601853    -0.78   0.443    -.7364668    .3312455
          9  |  -.3352016   .2545008    -1.32   0.199    -.8573941     .186991
         10  |  -.1544897   .2417927    -0.64   0.528    -.6506072    .3416279
         11  |  -.2233151   .3153223    -0.71   0.485    -.8703031    .4236729
         12  |  -.2618106   .2542377    -1.03   0.312    -.7834633     .259842
         13  |  -.1913936   .3121458    -0.61   0.545    -.8318638    .4490767
         14  |  -.0805847   .2450223    -0.33   0.745    -.5833289    .4221595
         15  |  -.1608265   .2055729    -0.78   0.441    -.5826273    .2609744
         16  |  -.2056501   .2358537    -0.87   0.391     -.689582    .2782817
         17  |  -.1353484   .2649751    -0.51   0.614    -.6790323    .4083355
         18  |  -.2382477   .2335074    -1.02   0.317    -.7173652    .2408698
         19  |  -.3603634     .27019    -1.33   0.193    -.9147474    .1940206
         20  |  -.2280712   .2873953    -0.79   0.434    -.8177575    .3616152
         21  |  -.1832497   .2733337    -0.67   0.508     -.744084    .3775847
         22  |  -.1591457   .2411038    -0.66   0.515    -.6538498    .3355584
         23  |  -.0601543   .2460372    -0.24   0.809    -.5649808    .4446723
         24  |   -.110078   .2728519    -0.40   0.690    -.6699239    .4497679
         25  |  -.1284312   .2349283    -0.55   0.589    -.6104644    .3536019
         26  |  -.1452572   .2706561    -0.54   0.596    -.7005977    .4100833
         27  |  -.1607851    .243651    -0.66   0.515    -.6607157    .3391454
         28  |  -.0753147   .2335689    -0.32   0.750    -.5545586    .4039292
         29  |  -.0929008   .2206807    -0.42   0.677    -.5457002    .3598986
         30  |  -.0453803   .2569278    -0.18   0.861    -.5725527    .4817921
         31  |   .0286763    .243163     0.12   0.907     -.470253    .5276055
         32  |  -.0158851   .2408965    -0.07   0.948    -.5101639    .4783936
         33  |  -.1033411   .2569002    -0.40   0.691    -.6304568    .4237747
         34  |  -.0537586   .2496191    -0.22   0.831    -.5659346    .4584174
         35  |  -.0527932   .2459943    -0.21   0.832    -.5575318    .4519454
         36  |  -.0466983   .2155592    -0.22   0.830    -.4889893    .3955927
         37  |   .0066726   .2202179     0.03   0.976    -.4451771    .4585224
         38  |  -.3968859   .2405477    -1.65   0.111    -.8904489    .0966772
         39  |  -.0743038   .2336372    -0.32   0.753    -.5536877    .4050801
         40  |  -.0740161   .2655359    -0.28   0.783    -.6188508    .4708185
         41  |  -.1325339   .2370672    -0.56   0.581    -.6189556    .3538879
         42  |   .0090977   .2529748     0.04   0.972    -.5099638    .5281592
         43  |    .021252   .2274371     0.09   0.926    -.4454104    .4879144
         44  |  -.0465118   .2542502    -0.18   0.856      -.56819    .4751665
         45  |   .0485628   .2629727     0.18   0.855    -.4910126    .5881382
         46  |  -.1204338   .2463008    -0.49   0.629    -.6258013    .3849338
         47  |   -.052932   .2451664    -0.22   0.831    -.5559719    .4501079
         48  |   .0521618    .243412     0.21   0.832    -.4472782    .5516019
         49  |    .028807   .2217425     0.13   0.898     -.426171     .483785
         50  |  -.0855249   .2166297    -0.39   0.696    -.5300124    .3589626
         51  |    .093391   .2189616     0.43   0.673    -.3558811     .542663
         52  |   .0328081   .2371262     0.14   0.891    -.4537347    .5193508
         53  |  -.0003092   .2060964    -0.00   0.999    -.4231842    .4225658
         54  |   .0373925   .2403146     0.16   0.878    -.4556923    .5304773
         55  |  -.0226623   .2402398    -0.09   0.926    -.5155936     .470269
         56  |   .2024278   .1725569     1.17   0.251    -.1516298    .5564853
         57  |  -.3960815   .2448724    -1.62   0.117    -.8985182    .1063553
         58  |   .5868039   .3703305     1.58   0.125    -.1730515    1.346659
         59  |   .0038043   .3837764     0.01   0.992    -.7836398    .7912483
         60  |   .1861313   .3560856     0.52   0.605    -.5444959    .9167586
         61  |   .3593174   .3736934     0.96   0.345    -.4074382    1.126073
         62  |  -.2857114   .2839552    -1.01   0.323    -.8683393    .2969164
         63  |  -.0505094   .3148151    -0.16   0.874    -.6964567    .5954379
         64  |   .0253363   .2549967     0.10   0.922    -.4978736    .5485462
         65  |  -.3282106   .2676649    -1.23   0.231    -.8774135    .2209924
         66  |  -.1059552   .2307001    -0.46   0.650    -.5793126    .3674023
         67  |  -.1787842   .2615856    -0.68   0.500    -.7155136    .3579452
         68  |   .0416178   .3574339     0.12   0.908    -.6917761    .7750116
         69  |   -.255296   .2468195    -1.03   0.310    -.7617279    .2511358
         70  |   .1193873   .3384727     0.35   0.727    -.5751013    .8138759
         71  |          0  (omitted)
             |
   prov2Xyob |   .0089868   .0043979     2.04   0.051    -.0000369    .0180105
   prov3Xyob |  -.0248304   .0024232   -10.25   0.000    -.0298023   -.0198584
   prov4Xyob |  -.0030259   .0037554    -0.81   0.427    -.0107314    .0046796
   prov5Xyob |  -.0052731   .0034418    -1.53   0.137     -.012335    .0017889
   prov6Xyob |   .0033398   .0017176     1.94   0.062    -.0001845    .0068641
   prov7Xyob |   .0070813   .0046431     1.53   0.139    -.0024456    .0166081
   prov8Xyob |  -.0031832   .0035308    -0.90   0.375    -.0104278    .0040613
   prov9Xyob |   -.002145   .0033043    -0.65   0.522    -.0089249    .0046349
  prov10Xyob |   -.005212   .0027037    -1.93   0.064    -.0107596    .0003355
  prov11Xyob |  -.0110234   .0031102    -3.54   0.001    -.0174049   -.0046419
  prov12Xyob |   .0396878   .0045397     8.74   0.000     .0303731    .0490025
  prov13Xyob |  -.0086569   .0024632    -3.51   0.002    -.0137109   -.0036028
  prov14Xyob |  -.0115175   .0037979    -3.03   0.005      -.01931   -.0037249
  prov15Xyob |   .0491294   .0039692    12.38   0.000     .0409854    .0572735
  prov16Xyob |  -.0052211   .0031974    -1.63   0.114    -.0117817    .0013395
  prov17Xyob |   .0036477   .0026348     1.38   0.178    -.0017584    .0090538
  prov18Xyob |  -.0067092   .0029507    -2.27   0.031    -.0127636   -.0006548
  prov19Xyob |  -.0068407    .002708    -2.53   0.018    -.0123971   -.0012843
  prov20Xyob |   .0056595   .0020632     2.74   0.011     .0014261    .0098929
  prov21Xyob |  -.0018621   .0040248    -0.46   0.647    -.0101203    .0063962
  prov22Xyob |   .0007844    .003319     0.24   0.815    -.0060257    .0075944
  prov23Xyob |  -.0016421   .0030365    -0.54   0.593    -.0078725    .0045883
  prov24Xyob |  -.0106271   .0041607    -2.55   0.017    -.0191642     -.00209
  prov25Xyob |   .0449275   .0034275    13.11   0.000     .0378948    .0519602
  prov26Xyob |   .0130016   .0041572     3.13   0.004     .0044718    .0215314
  prov27Xyob |   .0108934    .002111     5.16   0.000     .0065619    .0152249
  prov28Xyob |   .0085788   .0020504     4.18   0.000     .0043717    .0127859
       _cons |   .7677571   .2528424     3.04   0.005     .2489674    1.286547
------------------------------------------------------------------------------

. outreg2 using "table1_2.xls", keep(fine_e) append dec(3)
table1_2.xls
dir : seeout

. reg twins fine_e fine_exhan $control_1 [aw = weight], cluster(cluster_id)
(sum of wgt is   6.8777e+06)
note: 71.cell omitted because of collinearity

Linear regression                                      Number of obs = 6071862
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.0011
                                                       Root MSE      =  7.5708

                            (Std. Err. adjusted for 28 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
       twins |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      fine_e |   .0214112   .0349773     0.61   0.546    -.0503562    .0931786
  fine_exhan |   .0522837   .0157373     3.32   0.003     .0199934    .0845741
       rural |  -.0612743   .0152187    -4.03   0.000    -.0925004   -.0300482
    h_fm_han |   .0400743   .0266704     1.50   0.145    -.0146489    .0947974
             |
     h_m_edu |
          2  |   .0484254   .0119812     4.04   0.000     .0238419    .0730088
          3  |    .070609   .0197883     3.57   0.001     .0300068    .1112112
          4  |   .0410384   .0193774     2.12   0.044     .0012792    .0807975
             |
       order |
          2  |   .2196409   .0343417     6.40   0.000     .1491775    .2901042
          3  |   .1996275   .0224955     8.87   0.000     .1534706    .2457843
             |
 m_birth_age |
         17  |   .0256482   .0734981     0.35   0.730    -.1251574    .1764539
         18  |   .0654947   .0587519     1.11   0.275    -.0550543    .1860436
         19  |   .0545884   .0666661     0.82   0.420    -.0821991    .1913759
         20  |   .0780069   .0641977     1.22   0.235    -.0537159    .2097296
         21  |   .1090649   .0601999     1.81   0.081    -.0144552    .2325849
         22  |   .1489958   .0586795     2.54   0.017     .0285954    .2693962
         23  |   .1874158    .055245     3.39   0.002     .0740625    .3007691
         24  |   .1951189   .0606699     3.22   0.003     .0706346    .3196032
         25  |   .2275007   .0574961     3.96   0.000     .1095285     .345473
         26  |    .274623   .0566057     4.85   0.000     .1584778    .3907683
         27  |    .294878   .0527881     5.59   0.000     .1865657    .4031902
         28  |   .3270684   .0681286     4.80   0.000     .1872801    .4668567
         29  |   .3488617   .0584498     5.97   0.000     .2289327    .4687908
         30  |   .3322856   .0699094     4.75   0.000     .1888433    .4757278
         31  |   .4956043   .0892203     5.55   0.000     .3125395    .6786691
         32  |   .3709728   .0888249     4.18   0.000     .1887192    .5532265
         33  |   .3305003   .0931163     3.55   0.001     .1394414    .5215592
         34  |   .4781837   .1429344     3.35   0.002     .1849065    .7714609
         35  |   .6789831   .1889814     3.59   0.001     .2912254    1.066741
         36  |   .2315507   .1381483     1.68   0.105    -.0519062    .5150075
         37  |   .2873358   .2856498     1.01   0.323    -.2987693    .8734408
         38  |   .3977545   .2209776     1.80   0.083    -.0556542    .8511631
         39  |   .0180814   .2058452     0.09   0.931    -.4042782    .4404409
         40  |   .7154647   .5157549     1.39   0.177     -.342777    1.773706
         41  |   .5393745   .5105592     1.06   0.300    -.5082063    1.586955
         42  |    .401155    .290205     1.38   0.178    -.1942965    .9966065
         43  |   .2668914   .3075763     0.87   0.393     -.364203    .8979858
         44  |  -.0332825    .253879    -0.13   0.897    -.5541992    .4876342
         45  |   .0479228   .3246697     0.15   0.884    -.6182445      .71409
         46  |  -.3432104   .0660488    -5.20   0.000    -.4787313   -.2076895
         47  |   .4081456    .606972     0.67   0.507    -.8372581    1.653549
         48  |  -.3030887   .0671258    -4.52   0.000    -.4408195   -.1653578
         49  |   .8939774   1.207795     0.74   0.466    -1.584214    3.372169
         50  |  -.2134224   .0626123    -3.41   0.002    -.3418921   -.0849527
             |
 birth_month |
          1  |  -.6647636   .2800397    -2.37   0.025    -1.239358   -.0901695
          2  |  -.6593877    .276845    -2.38   0.025    -1.227427   -.0913487
          3  |  -.6261778   .2732195    -2.29   0.030    -1.186778   -.0655776
          4  |  -.6339193   .2767766    -2.29   0.030    -1.201818   -.0660206
          5  |  -.6149856   .2806379    -2.19   0.037    -1.190807   -.0391643
          6  |  -.5906175   .2750448    -2.15   0.041    -1.154963   -.0262723
          7  |  -.6121867   .2736872    -2.24   0.034    -1.173746   -.0506271
          8  |  -.6100964    .272184    -2.24   0.033    -1.168572    -.051621
          9  |   -.630749   .2806328    -2.25   0.033     -1.20656   -.0549382
         10  |  -.6351475   .2744582    -2.31   0.029    -1.198289   -.0720058
         11  |  -.6674764    .274346    -2.43   0.022    -1.230388   -.1045649
         12  |  -.6428246   .2772191    -2.32   0.028    -1.211631   -.0740179
             |
        prov |
         12  |  -.1650749   .0960967    -1.72   0.097    -.3622491    .0320994
         13  |  -.2366923   .0442691    -5.35   0.000    -.3275251   -.1458596
         14  |  -.3201727   .0797934    -4.01   0.000    -.4838952   -.1564501
         15  |   .0063512   .0684669     0.09   0.927    -.1341312    .1468336
         21  |   -.080132    .014226    -5.63   0.000    -.1093212   -.0509427
         22  |  -.1620206   .0889862    -1.82   0.080    -.3446052    .0205639
         23  |  -.0062595   .0676802    -0.09   0.927    -.1451278    .1326087
         31  |  -.0726914   .0391608    -1.86   0.074    -.1530428    .0076599
         32  |  -.2462141   .0364294    -6.76   0.000    -.3209612   -.1714671
         33  |  -.1761018   .0460657    -3.82   0.001    -.2706208   -.0815827
         34  |   -.318422   .0797188    -3.99   0.000    -.4819914   -.1548527
         35  |  -.1719643   .0364073    -4.72   0.000    -.2466659   -.0972627
         36  |  -.3013416   .0595142    -5.06   0.000    -.4234546   -.1792285
         37  |  -.1740969   .0764367    -2.28   0.031     -.330932   -.0172617
         41  |  -.2938261   .0566509    -5.19   0.000    -.4100642   -.1775879
         42  |   .0278401   .0424161     0.66   0.517    -.0591905    .1148707
         43  |  -.2335905   .0466168    -5.01   0.000    -.3292403   -.1379407
         44  |  -.2641387   .0355753    -7.42   0.000    -.3371333   -.1911441
         45  |  -.1994942   .0280773    -7.11   0.000     -.257104   -.1418844
         51  |  -.3458893   .0599287    -5.77   0.000    -.4688528   -.2229259
         52  |   -.296528    .063772    -4.65   0.000    -.4273773   -.1656786
         53  |  -.2094549   .0567045    -3.69   0.001    -.3258029   -.0931069
         61  |  -.3175579   .0617265    -5.14   0.000    -.4442102   -.1909055
         62  |  -.3240591   .0674338    -4.81   0.000    -.4624217   -.1856964
         63  |  -.4766572   .0819641    -5.82   0.000    -.6448337   -.3084806
         64  |  -.1936256   .0416509    -4.65   0.000    -.2790862   -.1081651
         65  |  -.1431442   .0388575    -3.68   0.001    -.2228733   -.0634152
             |
        cell |
          2  |  -.1071159   .0482012    -2.22   0.035    -.2060166   -.0082152
          3  |  -.2379365   .0436282    -5.45   0.000    -.3274542   -.1484188
          4  |  -.2126714   .0492627    -4.32   0.000      -.31375   -.1115927
          5  |  -.1853573   .0405567    -4.57   0.000    -.2685729   -.1021417
          6  |    -.16877   .0439598    -3.84   0.001     -.258968   -.0785719
          7  |  -.2384139   .0453651    -5.26   0.000    -.3314955   -.1453324
          8  |  -.2500352   .0496362    -5.04   0.000    -.3518803   -.1481901
          9  |  -.2656948   .0582694    -4.56   0.000    -.3852538   -.1461358
         10  |  -.2598065   .0612162    -4.24   0.000    -.3854117   -.1342013
         11  |  -.3236033   .0633098    -5.11   0.000    -.4535042   -.1937023
         12  |  -.2686044   .0585417    -4.59   0.000    -.3887221   -.1484866
         13  |  -.2988193   .0570548    -5.24   0.000    -.4158861   -.1817525
         14  |  -.2959457   .0711903    -4.16   0.000     -.442016   -.1498753
         15  |  -.3088243   .0739776    -4.17   0.000    -.4606138   -.1570349
         16  |  -.3448131   .0854369    -4.04   0.000    -.5201152   -.1695109
         17  |  -.3881469    .106313    -3.65   0.001    -.6062831   -.1700107
         18  |  -.4103963   .1101147    -3.73   0.001     -.636333   -.1844595
         19  |   .4488709    .255853     1.75   0.091     -.076096    .9738378
         20  |   .3784335   .2628783     1.44   0.161    -.1609483    .9178152
         21  |   .3227468   .2585133     1.25   0.223    -.2076787    .8531722
         22  |   .2662355   .2345352     1.14   0.266     -.214991     .747462
         23  |   .2828958   .2391264     1.18   0.247    -.2077511    .7735427
         24  |   .2486155   .2366489     1.05   0.303    -.2369479     .734179
         25  |   .2704576   .2286882     1.18   0.247    -.1987717    .7396869
         26  |   .2478512   .2311384     1.07   0.293    -.2264057     .722108
         27  |   .2176432   .2094347     1.04   0.308    -.2120814    .6473677
         28  |   .1962902   .1770516     1.11   0.277    -.1669897    .5595701
         29  |   .2287661   .1942398     1.18   0.249     -.169781    .6273132
         30  |   .2207539   .1914801     1.15   0.259    -.1721308    .6136387
         31  |     .26717   .1959254     1.36   0.184    -.1348356    .6691757
         32  |   .2821794   .1988545     1.42   0.167    -.1258364    .6901952
         33  |   .2963129   .2013603     1.47   0.153    -.1168443    .7094701
         34  |   .3118596   .1975507     1.58   0.126    -.0934809    .7172001
         35  |   .3309575   .2033732     1.63   0.115    -.0863299    .7482449
         36  |   .2996233   .2008568     1.49   0.147    -.1125009    .7117475
         37  |   .3821083   .1905074     2.01   0.055    -.0087807    .7729973
         38  |   .1713636    .199035     0.86   0.397    -.2370225    .5797497
         39  |   .2670453   .2027446     1.32   0.199    -.1489522    .6830428
         40  |    .299126   .1970365     1.52   0.141    -.1051594    .7034114
         41  |   .2876756   .2061971     1.40   0.174    -.1354059    .7107572
         42  |   .2974782   .2002189     1.49   0.149    -.1133371    .7082935
         43  |   .2937356   .1872568     1.57   0.128    -.0904836    .6779549
         44  |   .3408196   .1927881     1.77   0.088    -.0547489    .7363881
         45  |   .3874702   .1947626     1.99   0.057    -.0121496      .78709
         46  |   .3042115   .1780206     1.71   0.099    -.0610565    .6694796
         47  |   .2971957   .1635394     1.82   0.080    -.0383594    .6327507
         48  |   .2995032   .1515258     1.98   0.058     -.011402    .6104084
         49  |   .2944091   .1580557     1.86   0.073    -.0298944    .6187125
         50  |   .2338314   .1315892     1.78   0.087    -.0361673      .50383
         51  |   .1898159   .1235855     1.54   0.136    -.0637605    .4433923
         52  |   .1927772    .113411     1.70   0.101    -.0399231    .4254774
         53  |   .1777046   .1142652     1.56   0.132    -.0567483    .4121575
         54  |   .1413619   .1077396     1.31   0.201    -.0797014    .3624253
         55  |   .1239227   .1149905     1.08   0.291    -.1120183    .3598638
         56  |   .1802644    .121594     1.48   0.150    -.0692259    .4297547
         57  |    .117628    .244542     0.48   0.634    -.3841308    .6193868
         58  |   .2837204   .1784402     1.59   0.123    -.0824087    .6498496
         59  |     .21616   .1823058     1.19   0.246    -.1579005    .5902205
         60  |   .2937872   .1940679     1.51   0.142    -.1044072    .6919815
         61  |   .1056688   .1444737     0.73   0.471    -.1907669    .4021044
         62  |    .092128   .1741325     0.53   0.601    -.2651624    .4494183
         63  |   .1372076   .1401933     0.98   0.336    -.1504453    .4248605
         64  |   .0714436    .154625     0.46   0.648    -.2458208    .3887079
         65  |   .1056876   .1349862     0.78   0.440    -.1712813    .3826565
         66  |   .0760339   .1665637     0.46   0.652    -.2657266    .4177945
         67  |    .092801   .1350264     0.69   0.498    -.1842503    .3698523
         68  |   .1145296   .1373499     0.83   0.412    -.1672892    .3963483
         69  |  -.0282901   .1085734    -0.26   0.796    -.2510643     .194484
         70  |   .0336052   .1240235     0.27   0.788    -.2208701    .2880805
         71  |          0  (omitted)
             |
   prov2Xyob |   .0114091   .0058714     1.94   0.062    -.0006381    .0234562
   prov3Xyob |   .0200337   .0025202     7.95   0.000     .0148626    .0252047
   prov4Xyob |   .0229466   .0049199     4.66   0.000     .0128518    .0330413
   prov5Xyob |   .0079333   .0042251     1.88   0.071    -.0007359    .0166026
   prov6Xyob |   .0061767   .0007398     8.35   0.000     .0046587    .0076946
   prov7Xyob |   .0174263    .005926     2.94   0.007     .0052671    .0295856
   prov8Xyob |   .0088866   .0043459     2.04   0.051    -.0000304    .0178035
   prov9Xyob |   .0059292     .00307     1.93   0.064      -.00037    .0122283
  prov10Xyob |   .0231446    .002261    10.24   0.000     .0185054    .0277838
  prov11Xyob |   .0107951   .0030383     3.55   0.001      .004561    .0170293
  prov12Xyob |    .024239   .0056049     4.32   0.000     .0127387    .0357393
  prov13Xyob |    .018265   .0022869     7.99   0.000     .0135727    .0229573
  prov14Xyob |    .014258   .0036693     3.89   0.001     .0067292    .0217868
  prov15Xyob |   .0259433   .0046949     5.53   0.000     .0163102    .0355765
  prov16Xyob |   .0311831   .0036195     8.62   0.000     .0237565    .0386097
  prov17Xyob |   .0019855   .0025265     0.79   0.439    -.0031985    .0071695
  prov18Xyob |   .0104603   .0034974     2.99   0.006     .0032843    .0176363
  prov19Xyob |   .0181218   .0019289     9.39   0.000      .014164    .0220796
  prov20Xyob |   .0142844   .0015713     9.09   0.000     .0110603    .0175084
  prov21Xyob |   .0195692   .0040812     4.79   0.000     .0111952    .0279431
  prov22Xyob |   .0172841   .0037833     4.57   0.000     .0095214    .0250469
  prov23Xyob |    .008434   .0034537     2.44   0.021     .0013476    .0155203
  prov24Xyob |    .019984   .0042041     4.75   0.000     .0113578    .0286102
  prov25Xyob |   .0222676   .0040055     5.56   0.000     .0140489    .0304863
  prov26Xyob |   .0255447    .005174     4.94   0.000     .0149285    .0361609
  prov27Xyob |   .0127361   .0018829     6.76   0.000     .0088727    .0165995
  prov28Xyob |   .0143832   .0021932     6.56   0.000     .0098832    .0188832
       _cons |   .4178104   .0975475     4.28   0.000     .2176595    .6179614
------------------------------------------------------------------------------

. outreg2 using "table1_2.xls", keep(fine_e fine_exhan ) append  dec(3)
table1_2.xls
dir : seeout

. reg twins policyxhan $control_1 [aw = weight], cluster(cluster_id)
(sum of wgt is   6.8777e+06)
note: 71.cell omitted because of collinearity

Linear regression                                      Number of obs = 6071862
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.0011
                                                       Root MSE      =  7.5708

                            (Std. Err. adjusted for 28 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
       twins |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  policyxhan |   .1543031   .0297282     5.19   0.000      .093306    .2153002
       rural |  -.0622041    .015599    -3.99   0.000    -.0942105   -.0301976
    h_fm_han |  -.0153399   .0271609    -0.56   0.577    -.0710695    .0403898
             |
     h_m_edu |
          2  |   .0484244   .0118503     4.09   0.000     .0241095    .0727393
          3  |   .0703043   .0196497     3.58   0.001     .0299866    .1106221
          4  |   .0406029   .0193358     2.10   0.045     .0009291    .0802766
             |
       order |
          2  |   .2199289   .0344182     6.39   0.000     .1493086    .2905491
          3  |   .2004849   .0225149     8.90   0.000     .1542881    .2466816
             |
 m_birth_age |
         17  |   .0254683   .0736498     0.35   0.732    -.1256487    .1765852
         18  |   .0652034    .059032     1.10   0.279    -.0559204    .1863271
         19  |   .0541822   .0667797     0.81   0.424    -.0828385    .1912029
         20  |   .0780391   .0642447     1.21   0.235    -.0537801    .2098583
         21  |    .109211   .0601786     1.81   0.081    -.0142652    .2326872
         22  |   .1491496   .0586721     2.54   0.017     .0287644    .2695348
         23  |   .1876954   .0552861     3.39   0.002     .0742578    .3011331
         24  |   .1951263   .0606404     3.22   0.003     .0707026      .31955
         25  |   .2272316   .0572959     3.97   0.000     .1096702     .344793
         26  |   .2743251   .0564085     4.86   0.000     .1585843    .3900658
         27  |   .2945135   .0526703     5.59   0.000      .186443    .4025841
         28  |    .326865   .0681583     4.80   0.000     .1870157    .4667143
         29  |   .3494533   .0584017     5.98   0.000     .2296229    .4692836
         30  |   .3325226   .0698067     4.76   0.000     .1892911     .475754
         31  |   .4956154   .0890465     5.57   0.000      .312907    .6783237
         32  |   .3715539   .0891833     4.17   0.000     .1885649    .5545428
         33  |   .3306591   .0929761     3.56   0.001     .1398878    .5214303
         34  |   .4774328   .1426762     3.35   0.002     .1846854    .7701802
         35  |   .6782892   .1894379     3.58   0.001     .2895947    1.066984
         36  |   .2320338   .1381031     1.68   0.104    -.0513303    .5153979
         37  |   .2889595   .2852609     1.01   0.320    -.2963475    .8742665
         38  |   .3990745   .2205138     1.81   0.081    -.0533825    .8515315
         39  |    .018661   .2057994     0.09   0.928    -.4036045    .4409266
         40  |   .7177069   .5155163     1.39   0.175    -.3400453    1.775459
         41  |   .5385027   .5099197     1.06   0.300    -.5077662    1.584772
         42  |   .4045252   .2906381     1.39   0.175    -.1918149    1.000865
         43  |   .2702557   .3089579     0.87   0.389    -.3636736    .9041849
         44  |  -.0331261   .2538803    -0.13   0.897    -.5540455    .4877933
         45  |     .04664   .3240841     0.14   0.887    -.6183257    .7116057
         46  |  -.3474692   .0663233    -5.24   0.000    -.4835533   -.2113851
         47  |   .4188625   .6169506     0.68   0.503    -.8470155    1.684741
         48  |   -.297192   .0648081    -4.59   0.000    -.4301673   -.1642168
         49  |   .8917312   1.207924     0.74   0.467    -1.586725    3.370187
         50  |  -.2134973   .0616028    -3.47   0.002    -.3398958   -.0870987
             |
 birth_month |
          1  |  -.4108493   .1207084    -3.40   0.002    -.6585224   -.1631763
          2  |  -.4048061   .1132536    -3.57   0.001    -.6371834   -.1724289
          3  |  -.3711707   .1138492    -3.26   0.003    -.6047699   -.1375715
          4  |  -.3781226   .1128885    -3.35   0.002    -.6097506   -.1464946
          5  |  -.3588807   .1188409    -3.02   0.005     -.602722   -.1150394
          6  |  -.3343659    .110179    -3.03   0.005    -.5604345   -.1082973
          7  |  -.3554766   .1114948    -3.19   0.004     -.584245   -.1267082
          8  |  -.3529793   .1102237    -3.20   0.003    -.5791396   -.1268191
          9  |  -.3731958   .1155124    -3.23   0.003    -.6102077   -.1361838
         10  |  -.3771889    .110093    -3.43   0.002     -.603081   -.1512968
         11  |  -.4090313   .1096071    -3.73   0.001    -.6339266   -.1841361
         12  |   -.383618   .1127072    -3.40   0.002    -.6148741   -.1523619
             |
        prov |
         12  |    .000792   .0122135     0.06   0.949     -.024268    .0258521
         13  |  -.1481956   .0105943   -13.99   0.000    -.1699334   -.1264578
         14  |  -.1728055   .0109891   -15.73   0.000    -.1953532   -.1502577
         15  |   .1271872   .0113931    11.16   0.000     .1038105    .1505639
         21  |    -.04758   .0108115    -4.40   0.000    -.0697634   -.0253966
         22  |   .0077015   .0096786     0.80   0.433    -.0121574    .0275604
         23  |   .1265504    .011864    10.67   0.000     .1022075    .1508932
         31  |   .0033276   .0047642     0.70   0.491    -.0064478    .0131029
         32  |   -.167387    .012935   -12.94   0.000    -.1939274   -.1408466
         33  |  -.0829357   .0143448    -5.78   0.000    -.1123689   -.0535026
         34  |  -.1681933   .0098146   -17.14   0.000    -.1883312   -.1480554
         35  |  -.0988578   .0120975    -8.17   0.000    -.1236797   -.0740359
         36  |  -.1824174   .0125503   -14.53   0.000    -.2081685   -.1566663
         37  |  -.0280786   .0095631    -2.94   0.007    -.0477005   -.0084567
         41  |  -.1814117   .0109575   -16.56   0.000    -.2038945   -.1589289
         42  |   .1141267   .0102468    11.14   0.000      .093102    .1351514
         43  |  -.1384611   .0141272    -9.80   0.000    -.1674476   -.1094746
         44  |  -.2060634   .0130036   -15.85   0.000    -.2327445   -.1793822
         45  |  -.1587157   .0118157   -13.43   0.000    -.1829595   -.1344718
         51  |  -.2250753   .0117555   -19.15   0.000    -.2491956    -.200955
         52  |   -.196529   .0138635   -14.18   0.000    -.2249745   -.1680835
         53  |  -.1254416   .0180995    -6.93   0.000    -.1625787   -.0883046
         61  |  -.2036397   .0088865   -22.92   0.000    -.2218732   -.1854062
         62  |  -.2122407   .0148055   -14.34   0.000    -.2426191   -.1818623
         63  |  -.3583613   .0215337   -16.64   0.000    -.4025448   -.3141777
         64  |  -.1383036   .0218981    -6.32   0.000    -.1832348   -.0933724
         65  |  -.0771469   .0112476    -6.86   0.000    -.1002251   -.0540687
             |
        cell |
          2  |  -.1010402   .0480554    -2.10   0.045    -.1996417   -.0024387
          3  |  -.2254119    .042971    -5.25   0.000     -.313581   -.1372428
          4  |  -.1937084   .0490587    -3.95   0.001    -.2943685   -.0930483
          5  |  -.1600225   .0357094    -4.48   0.000     -.233292   -.0867529
          6  |  -.1372494    .038347    -3.58   0.001    -.2159309   -.0585679
          7  |  -.2004787   .0432077    -4.64   0.000    -.2891336   -.1118239
          8  |  -.2055816   .0409588    -5.02   0.000     -.289622   -.1215411
          9  |  -.2147591   .0480142    -4.47   0.000    -.3132761   -.1162421
         10  |   -.202213   .0477375    -4.24   0.000    -.3001623   -.1042637
         11  |  -.2596635   .0467455    -5.55   0.000    -.3555773   -.1637497
         12  |  -.1981095   .0415083    -4.77   0.000    -.2832774   -.1129415
         13  |  -.2216909   .0392163    -5.65   0.000    -.3021561   -.1412257
         14  |  -.2124456   .0456991    -4.65   0.000    -.3062124   -.1186788
         15  |  -.2188793   .0574795    -3.81   0.001    -.3368176    -.100941
         16  |  -.3526479   .0623482    -5.66   0.000    -.4805759   -.2247199
         17  |  -.3485245   .0596277    -5.85   0.000    -.4708704   -.2261787
         18  |  -.3647126   .0553496    -6.59   0.000    -.4782807   -.2511446
         19  |   .2353267    .118458     1.99   0.057    -.0077291    .4783825
         20  |   .1723793   .1150297     1.50   0.146    -.0636422    .4084008
         21  |   .1232361   .1260978     0.98   0.337    -.1354952    .3819674
         22  |   .0731469   .1099123     0.67   0.511    -.1523746    .2986684
         23  |   .0964842   .1165054     0.83   0.415    -.1425651    .3355336
         24  |   .0686069   .1175036     0.58   0.564    -.1724906    .3097045
         25  |   .0968069   .1149104     0.84   0.407    -.1389698    .3325837
         26  |   .0825722   .1142046     0.72   0.476    -.1517563    .3169007
         27  |  -.0294442   .1111996    -0.26   0.793    -.2576069    .1987186
         28  |  -.0205814   .0980033    -0.21   0.835    -.2216675    .1805047
         29  |   .0177052   .1108628     0.16   0.874    -.2097664    .2451768
         30  |   .0091983   .1145302     0.08   0.937    -.2257981    .2441948
         31  |   .0597426   .1125452     0.53   0.600    -.1711812    .2906663
         32  |   .0785183   .1201215     0.65   0.519    -.1679506    .3249873
         33  |   .0976235   .1231673     0.79   0.435     -.155095     .350342
         34  |     .12011   .1246807     0.96   0.344    -.1357138    .3759337
         35  |   .1489513   .1303526     1.14   0.263    -.1185102    .4164128
         36  |   .1257688   .1301124     0.97   0.342    -.1411998    .3927374
         37  |   .2232576    .135401     1.65   0.111    -.0545624    .5010776
         38  |  -.0433781   .1294875    -0.33   0.740    -.3090645    .2223084
         39  |   .0547098   .1205259     0.45   0.654    -.1925889    .3020085
         40  |   .0909132   .1191368     0.76   0.452    -.1535354    .3353617
         41  |   .0839295   .1249789     0.67   0.508     -.172506     .340365
         42  |   .1001237   .1238847     0.81   0.426    -.1540667     .354314
         43  |   .1031128    .118251     0.87   0.391    -.1395183    .3457439
         44  |   .1586704   .1248461     1.27   0.215    -.0974925    .4148333
         45  |   .2129296   .1267185     1.68   0.104    -.0470753    .4729345
         46  |   .1476878   .1209309     1.22   0.233     -.100442    .3958175
         47  |   .1662225   .1167474     1.42   0.166    -.0733235    .4057684
         48  |   .1917077   .1164267     1.65   0.111    -.0471802    .4305956
         49  |   .2116597   .1365441     1.55   0.133    -.0685058    .4918251
         50  |   .1635892   .1146721     1.43   0.165    -.0716985    .3988769
         51  |   .1301342   .1137947     1.14   0.263    -.1033533    .3636217
         52  |   .1427097   .1027974     1.39   0.176    -.0682131    .3536324
         53  |   .1341035   .1090402     1.23   0.229    -.0896286    .3578356
         54  |   .1092994   .1021315     1.07   0.294    -.1002571    .3188559
         55  |   .1084344   .1118116     0.97   0.341    -.1209839    .3378528
         56  |   .1738395   .1194004     1.46   0.157    -.0711499     .418829
         57  |  -.0765998   .2014644    -0.38   0.707    -.4899706     .336771
         58  |   .1005186   .1153921     0.87   0.391    -.1362463    .3372836
         59  |   .0388041   .1203907     0.32   0.750    -.2082172    .2858254
         60  |   .1313443   .1328672     0.99   0.332    -.1412766    .4039652
         61  |  -.0337998   .1007182    -0.34   0.740    -.2404564    .1728568
         62  |  -.0237794   .1338048    -0.18   0.860    -.2983241    .2507654
         63  |   .0572788   .1196658     0.48   0.636    -.1882553    .3028128
         64  |   .0085492   .1432801     0.06   0.953    -.2854374    .3025357
         65  |   .0524647   .1231763     0.43   0.674    -.2002722    .3052017
         66  |   .0319566   .1629093     0.20   0.846    -.3023057    .3662189
         67  |   .0548988   .1321996     0.42   0.681    -.2163524      .32615
         68  |    .086338   .1376024     0.63   0.536    -.1959988    .3686748
         69  |  -.0427592   .1077861    -0.40   0.695     -.263918    .1783997
         70  |   .0276406   .1230086     0.22   0.824    -.2247523    .2800335
         71  |          0  (omitted)
             |
   prov2Xyob |   .0010537   .0005772     1.83   0.079    -.0001306     .002238
   prov3Xyob |   .0149856    .000756    19.82   0.000     .0134345    .0165367
   prov4Xyob |   .0138784   .0003333    41.64   0.000     .0131945    .0145623
   prov5Xyob |   .0004011   .0003444     1.16   0.254    -.0003055    .0011077
   prov6Xyob |   .0047987   .0006036     7.95   0.000     .0035602    .0060372
   prov7Xyob |   .0062785   .0004025    15.60   0.000     .0054526    .0071045
   prov8Xyob |   .0004516   .0005363     0.84   0.407    -.0006489    .0015521
   prov9Xyob |   .0001083   .0002865     0.38   0.708    -.0004796    .0006962
  prov10Xyob |   .0183745   .0007598    24.18   0.000     .0168155    .0199334
  prov11Xyob |   .0046768   .0006289     7.44   0.000     .0033865    .0059672
  prov12Xyob |   .0134666    .000478    28.17   0.000     .0124857    .0144474
  prov13Xyob |   .0134266    .000691    19.43   0.000     .0120088    .0148443
  prov14Xyob |   .0068631   .0006129    11.20   0.000     .0056055    .0081206
  prov15Xyob |   .0168036   .0006187    27.16   0.000     .0155342    .0180731
  prov16Xyob |   .0240427   .0007453    32.26   0.000     .0225135    .0255718
  prov17Xyob |  -.0032757   .0006962    -4.71   0.000    -.0047042   -.0018473
  prov18Xyob |   .0035126   .0007908     4.44   0.000     .0018901    .0051352
  prov19Xyob |   .0147926   .0004616    32.05   0.000     .0138455    .0157396
  prov20Xyob |   .0118111   .0006429    18.37   0.000      .010492    .0131301
  prov21Xyob |   .0115655   .0006149    18.81   0.000     .0103038    .0128272
  prov22Xyob |   .0109162   .0004854    22.49   0.000     .0099202    .0119122
  prov23Xyob |   .0028596   .0006372     4.49   0.000     .0015523     .004167
  prov24Xyob |   .0120725   .0002762    43.71   0.000     .0115058    .0126391
  prov25Xyob |   .0152448   .0004594    33.18   0.000     .0143021    .0161875
  prov26Xyob |   .0174694   .0007757    22.52   0.000     .0158777    .0190611
  prov27Xyob |   .0098902   .0008385    11.80   0.000     .0081698    .0116107
  prov28Xyob |   .0105549   .0005297    19.93   0.000     .0094681    .0116417
       _cons |     .37647   .0833612     4.52   0.000     .2054269    .5475131
------------------------------------------------------------------------------

. outreg2 using "table1_2.xls", keep(policyxhan) append dec(3)
table1_2.xls
dir : seeout

. 
. /* Table 2 */ 
. reg twins order*Xfine_e i.order $control_1 [aw = weight] if h_fm_han == 1, cluster(cluster_id)
(sum of wgt is   6.3994e+06)
note: h_fm_han omitted because of collinearity
note: 71.cell omitted because of collinearity

Linear regression                                      Number of obs = 5654194
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.0011
                                                       Root MSE      =  7.6406

                             (Std. Err. adjusted for 28 clusters in cluster_id)
-------------------------------------------------------------------------------
              |               Robust
        twins |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
order1Xfine_e |   .0398416   .0414921     0.96   0.345    -.0452931    .1249763
order2Xfine_e |   .1509722      .0466     3.24   0.003     .0553568    .2465876
order3Xfine_e |   .0714424   .0453831     1.57   0.127    -.0216762    .1645609
              |
        order |
           2  |    .118037   .0257046     4.59   0.000     .0652956    .1707784
           3  |    .168163   .0230404     7.30   0.000      .120888     .215438
              |
        rural |  -.0588125   .0163351    -3.60   0.001    -.0923292   -.0252957
     h_fm_han |          0  (omitted)
              |
      h_m_edu |
           2  |   .0431472   .0127106     3.39   0.002     .0170673    .0692272
           3  |   .0663853   .0209551     3.17   0.004      .023389    .1093817
           4  |    .042046   .0194339     2.16   0.040     .0021711     .081921
              |
  m_birth_age |
          17  |     .00933   .0918716     0.10   0.920    -.1791751     .197835
          18  |   .0512862   .0739147     0.69   0.494    -.1003742    .2029467
          19  |   .0317989   .0817461     0.39   0.700    -.1359302    .1995281
          20  |   .0620868   .0793478     0.78   0.441    -.1007213     .224895
          21  |   .0931945    .076083     1.22   0.231    -.0629148    .2493038
          22  |   .1350529   .0730258     1.85   0.075    -.0147837    .2848895
          23  |   .1699766   .0693358     2.45   0.021     .0277113    .3122418
          24  |   .1781622    .076047     2.34   0.027     .0221266    .3341979
          25  |   .2174521    .073437     2.96   0.006     .0667719    .3681323
          26  |   .2645843   .0708748     3.73   0.001     .1191611    .4100075
          27  |   .2858454   .0683742     4.18   0.000     .1455532    .4261377
          28  |   .3120042   .0848943     3.68   0.001     .1378155    .4861929
          29  |   .3500365   .0687577     5.09   0.000     .2089574    .4911157
          30  |   .3207927   .0813629     3.94   0.001     .1538497    .4877356
          31  |   .5039338   .1025926     4.91   0.000     .2934312    .7144364
          32  |   .3853569   .1010239     3.81   0.001     .1780729    .5926409
          33  |   .3343146   .1028686     3.25   0.003     .1232456    .5453835
          34  |   .5177624   .1567359     3.30   0.003     .1961669    .8393579
          35  |   .7012697   .2100591     3.34   0.002      .270264    1.132275
          36  |   .2081888   .1409491     1.48   0.151    -.0810148    .4973924
          37  |   .3294872   .3188372     1.03   0.311    -.3247126    .9836871
          38  |   .3885843   .2280889     1.70   0.100    -.0794155    .8565841
          39  |   .0277032   .2290176     0.12   0.905    -.4422022    .4976086
          40  |   .6986816   .5512366     1.27   0.216    -.4323624    1.829726
          41  |   .0641921   .1713075     0.37   0.711    -.2873018     .415686
          42  |   .4389086   .3201868     1.37   0.182    -.2180604    1.095878
          43  |   .1084589   .2876302     0.38   0.709    -.4817095    .6986273
          44  |  -.0294403     .27749    -0.11   0.916    -.5988027    .5399221
          45  |   .0475688   .3587076     0.13   0.895    -.6884385     .783576
          46  |  -.3761807   .0725942    -5.18   0.000    -.5251316   -.2272298
          47  |  -.3348669   .0738211    -4.54   0.000    -.4863353   -.1833985
          48  |  -.3418596   .0741644    -4.61   0.000    -.4940324   -.1896869
          49  |   1.038791   1.371075     0.76   0.455    -1.774422    3.852004
          50  |  -.2326387   .0719746    -3.23   0.003    -.3803184   -.0849589
              |
  birth_month |
           1  |  -.5419576    .302893    -1.79   0.085    -1.163443    .0795276
           2  |  -.5403604   .2957646    -1.83   0.079    -1.147219    .0664984
           3  |  -.5106466   .2916798    -1.75   0.091    -1.109124    .0878309
           4  |  -.5166046   .2957758    -1.75   0.092    -1.123486    .0902771
           5  |  -.4976065   .3022622    -1.65   0.111    -1.117797    .1225843
           6  |  -.4636808   .2954102    -1.57   0.128    -1.069813    .1424509
           7  |  -.4929633    .294207    -1.68   0.105    -1.096626    .1106996
           8  |   -.487226   .2914293    -1.67   0.106     -1.08519    .1107376
           9  |  -.5083855   .3008087    -1.69   0.103    -1.125594     .108823
          10  |  -.5166864   .2931697    -1.76   0.089    -1.118221    .0848481
          11  |  -.5422205   .2944928    -1.84   0.077     -1.14647    .0620289
          12  |  -.5219536   .2966094    -1.76   0.090    -1.130546    .0866386
              |
         prov |
          12  |  -.0975971   .1011796    -0.96   0.343    -.3052004    .1100063
          13  |  -.1972433   .0509106    -3.87   0.001    -.3017032   -.0927833
          14  |  -.2577112   .0858517    -3.00   0.006    -.4338642   -.0815581
          15  |   .0402873   .0712687     0.57   0.577    -.1059439    .1865185
          21  |  -.0386282     .01767    -2.19   0.038     -.074884   -.0023724
          22  |  -.0902174   .0948846    -0.95   0.350    -.2849045    .1044697
          23  |   .0513612   .0726827     0.71   0.486    -.0977713    .2004937
          31  |  -.0477002   .0414036    -1.15   0.259    -.1326535     .037253
          32  |   -.201688   .0409382    -4.93   0.000    -.2856862   -.1176897
          33  |  -.1193924   .0516589    -2.31   0.029    -.2253878   -.0133971
          34  |  -.2575668    .086053    -2.99   0.006     -.434133   -.0810007
          35  |  -.1156907    .043716    -2.65   0.013    -.2053884    -.025993
          36  |  -.2368841   .0663869    -3.57   0.001    -.3730988   -.1006695
          37  |  -.1132159   .0823288    -1.38   0.180    -.2821406    .0557089
          41  |  -.2378871   .0635677    -3.74   0.001    -.3683172   -.1074571
          42  |   .0927234   .0479609     1.93   0.064    -.0056843    .1911311
          43  |  -.1824017   .0526312    -3.47   0.002     -.290392   -.0744114
          44  |  -.1994468   .0446377    -4.47   0.000    -.2910358   -.1078579
          45  |  -.1328104   .0337079    -3.94   0.001    -.2019732   -.0636475
          51  |  -.2983706   .0646201    -4.62   0.000    -.4309601    -.165781
          52  |    -.27068    .066309    -4.08   0.000     -.406735   -.1346251
          53  |  -.1599217   .0593374    -2.70   0.012    -.2816719   -.0381715
          61  |  -.2560856   .0674743    -3.80   0.001    -.3945314   -.1176397
          62  |  -.2205322   .0732759    -3.01   0.006     -.370882   -.0701824
          63  |  -.4274232   .0827474    -5.17   0.000    -.5972069   -.2576395
          64  |  -.0831044   .0411724    -2.02   0.054    -.1675831    .0013744
          65  |  -.0641808   .0353618    -1.81   0.081    -.1367373    .0083757
              |
         cell |
           2  |  -.0863255   .0516999    -1.67   0.107    -.1924048    .0197539
           3  |  -.1948677   .0449136    -4.34   0.000    -.2870228   -.1027125
           4  |  -.1631859   .0507558    -3.22   0.003    -.2673282   -.0590437
           5  |  -.1385316   .0447437    -3.10   0.005    -.2303382    -.046725
           6  |  -.1167717   .0478569    -2.44   0.022     -.214966   -.0185773
           7  |  -.1744811   .0452286    -3.86   0.001    -.2672825   -.0816797
           8  |  -.1838442   .0502402    -3.66   0.001    -.2869286   -.0807597
           9  |  -.1900835   .0560095    -3.39   0.002    -.3050055   -.0751615
          10  |  -.1911722    .063805    -3.00   0.006    -.3220893   -.0602551
          11  |  -.2529067   .0628191    -4.03   0.000    -.3818009   -.1240125
          12  |   -.190965   .0602308    -3.17   0.004    -.3145484   -.0673815
          13  |  -.2241585   .0672033    -3.34   0.002    -.3620483   -.0862688
          14  |  -.2253922   .0742223    -3.04   0.005    -.3776839   -.0731006
          15  |   -.230938    .072845    -3.17   0.004    -.3804035   -.0814724
          16  |  -.2690788   .0836535    -3.22   0.003    -.4407216   -.0974361
          17  |  -.3219472   .1091028    -2.95   0.006    -.5458077   -.0980867
          18  |  -.3352279   .1122115    -2.99   0.006    -.5654668   -.1049891
          19  |   .3698808      .2738     1.35   0.188    -.1919103     .931672
          20  |    .295522   .2799627     1.06   0.301    -.2789141    .8699581
          21  |   .2575256   .2757916     0.93   0.359    -.3083519    .8234031
          22  |   .2163866   .2504281     0.86   0.395    -.2974495    .7302226
          23  |   .2343018   .2560423     0.92   0.368    -.2910537    .7596573
          24  |   .2057639   .2514971     0.82   0.420    -.3102656    .7217933
          25  |   .2325853   .2448989     0.95   0.351    -.2699057    .7350763
          26  |   .2125896    .244981     0.87   0.393    -.2900698     .715249
          27  |   .1779983   .2244913     0.79   0.435    -.2826199    .6386165
          28  |   .1500664   .1908287     0.79   0.438    -.2414818    .5416145
          29  |   .1897667   .2078955     0.91   0.369    -.2367996     .616333
          30  |   .1810943   .2047522     0.88   0.384    -.2390224     .601211
          31  |    .228884   .2087598     1.10   0.283    -.1994557    .6572237
          32  |   .2523545   .2114866     1.19   0.243    -.1815801    .6862891
          33  |   .2783611   .2143146     1.30   0.205    -.1613762    .7180984
          34  |   .2940856   .2097037     1.40   0.172    -.1361909    .7243622
          35  |   .3180678   .2137556     1.49   0.148    -.1205225    .7566582
          36  |   .2877807   .2134037     1.35   0.189    -.1500875    .7256489
          37  |   .3762842   .2015474     1.87   0.073    -.0372569    .7898254
          38  |   .1504025   .2133603     0.70   0.487    -.2873767    .5881817
          39  |   .2339601   .2149956     1.09   0.286    -.2071744    .6750946
          40  |   .2705281   .2102791     1.29   0.209    -.1609291    .7019852
          41  |   .2658408   .2201518     1.21   0.238    -.1858734    .7175549
          42  |   .2693936   .2135809     1.26   0.218    -.1688381    .7076254
          43  |   .2681571   .2005821     1.34   0.192    -.1434033    .6797176
          44  |   .3284903   .2038695     1.61   0.119    -.0898154    .7467961
          45  |   .3746819   .2057994     1.82   0.080    -.0475836    .7969474
          46  |   .3012812   .1873989     1.61   0.120    -.0832295    .6857919
          47  |   .2932445   .1732008     1.69   0.102    -.0621342    .6486231
          48  |   .2912852    .159269     1.83   0.078    -.0355078    .6180782
          49  |   .2924427   .1689178     1.73   0.095     -.054148    .6390333
          50  |   .2416502   .1382613     1.75   0.092    -.0420386    .5253389
          51  |   .1801568   .1309258     1.38   0.180    -.0884808    .4487943
          52  |   .1933323   .1166046     1.66   0.109    -.0459206    .4325851
          53  |   .1839004   .1204067     1.53   0.138    -.0631536    .4309545
          54  |   .1417823   .1128283     1.26   0.220    -.0897223    .3732869
          55  |    .132047   .1203427     1.10   0.282    -.1148759    .3789699
          56  |   .1690927    .128755     1.31   0.200    -.0950908    .4332762
          57  |   .1037695   .2603413     0.40   0.693    -.4304066    .6379457
          58  |   .2257674   .1923678     1.17   0.251    -.1689388    .6204735
          59  |   .1944881   .1874202     1.04   0.309    -.1900664    .5790426
          60  |    .269399   .2065783     1.30   0.203    -.1544646    .6932626
          61  |   .0633264   .1495634     0.42   0.675    -.2435524    .3702052
          62  |   .0960241   .1858612     0.52   0.610    -.2853317    .4773799
          63  |   .1304334   .1500118     0.87   0.392    -.1773654    .4382322
          64  |   .0570425   .1668939     0.34   0.735    -.2853954    .3994805
          65  |   .1238926    .138403     0.90   0.379    -.1600869    .4078721
          66  |   .0784814   .1762688     0.45   0.660    -.2831922    .4401551
          67  |   .1073853    .135937     0.79   0.436    -.1715344     .386305
          68  |   .1121736   .1424343     0.79   0.438    -.1800774    .4044247
          69  |  -.0113176   .1101735    -0.10   0.919     -.237375    .2147397
          70  |   .0216798   .1327805     0.16   0.872    -.2507634     .294123
          71  |          0  (omitted)
              |
    prov2Xyob |   .0086098   .0061778     1.39   0.175     -.004066    .0212856
    prov3Xyob |   .0177808   .0030073     5.91   0.000     .0116103    .0239514
    prov4Xyob |   .0199165   .0053077     3.75   0.001     .0090259    .0308071
    prov5Xyob |   .0061234   .0044287     1.38   0.178    -.0029636    .0152103
    prov6Xyob |   .0034424   .0008741     3.94   0.001     .0016488     .005236
    prov7Xyob |   .0142652   .0062995     2.26   0.032     .0013397    .0271906
    prov8Xyob |   .0064038   .0046496     1.38   0.180    -.0031365     .015944
    prov9Xyob |   .0048056   .0032409     1.48   0.150    -.0018443    .0114554
   prov10Xyob |   .0212946   .0025247     8.43   0.000     .0161145    .0264748
   prov11Xyob |   .0082224   .0033586     2.45   0.021      .001331    .0151138
   prov12Xyob |   .0212835    .005977     3.56   0.001     .0090196    .0335474
   prov13Xyob |   .0156247   .0027639     5.65   0.000     .0099538    .0212957
   prov14Xyob |     .01109   .0041027     2.70   0.012      .002672     .019508
   prov15Xyob |   .0229451     .00506     4.53   0.000     .0125628    .0333273
   prov16Xyob |    .028328   .0040654     6.97   0.000     .0199864    .0366696
   prov17Xyob |   -.001128    .002902    -0.39   0.701    -.0070823    .0048263
   prov18Xyob |   .0081733   .0038529     2.12   0.043     .0002678    .0160787
   prov19Xyob |   .0147378   .0026686     5.52   0.000     .0092624    .0202133
   prov20Xyob |   .0117153   .0021951     5.34   0.000     .0072113    .0162192
   prov21Xyob |    .017476   .0043593     4.01   0.000     .0085314    .0264206
   prov22Xyob |   .0176471   .0040664     4.34   0.000     .0093035    .0259906
   prov23Xyob |     .00531   .0037059     1.43   0.163     -.002294    .0129139
   prov24Xyob |   .0170307   .0045682     3.73   0.001     .0076574    .0264039
   prov25Xyob |   .0169025   .0043855     3.85   0.001     .0079042    .0259008
   prov26Xyob |   .0244371   .0053782     4.54   0.000     .0134019    .0354722
   prov27Xyob |   .0062503   .0020654     3.03   0.005     .0020124    .0104881
   prov28Xyob |   .0118875   .0019533     6.09   0.000     .0078797    .0158953
        _cons |   .4142443   .0941567     4.40   0.000     .2210507    .6074379
-------------------------------------------------------------------------------

. outreg2 using "table1_2.xls", keep(order1Xfine_e order2Xfine_e order3Xfine_e) append dec(3)
table1_2.xls
dir : seeout

. reg twins fine_e i.order $control_1 [aw = weight] if h_fm_han == 1 & rural == 0, cluster(cluster_id)
(sum of wgt is   1.7749e+06)
note: rural omitted because of collinearity
note: h_fm_han omitted because of collinearity
note: 71.cell omitted because of collinearity

Linear regression                                      Number of obs = 1422621
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.0009
                                                       Root MSE      =  8.1067

                            (Std. Err. adjusted for 28 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
       twins |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      fine_e |   .0593264   .0413167     1.44   0.163    -.0254485    .1441012
             |
       order |
          2  |   .2086633   .0516822     4.04   0.000     .1026202    .3147063
          3  |   .1461026   .0535014     2.73   0.011     .0363268    .2558784
             |
       rural |          0  (omitted)
    h_fm_han |          0  (omitted)
             |
     h_m_edu |
          2  |   .0367554   .0340713     1.08   0.290    -.0331532    .1066639
          3  |   .0169773   .0428882     0.40   0.695    -.0710222    .1049767
          4  |  -.0644176   .0386748    -1.67   0.107    -.1437718    .0149366
             |
 m_birth_age |
         17  |   .0516552   .3125401     0.17   0.870    -.5896241    .6929345
         18  |  -.0588069   .3215311    -0.18   0.856    -.7185342    .6009204
         19  |  -.0910041   .3308163    -0.28   0.785    -.7697831    .5877749
         20  |  -.0052703   .3204391    -0.02   0.987    -.6627569    .6522164
         21  |   .0253165   .3214562     0.08   0.938    -.6342572    .6848902
         22  |    .077715   .3227902     0.24   0.812    -.5845957    .7400257
         23  |   .0625045   .3264605     0.19   0.850    -.6073371     .732346
         24  |   .0528098    .326191     0.16   0.873    -.6164789    .7220985
         25  |   .0932367   .3336341     0.28   0.782    -.5913238    .7777973
         26  |   .1817908    .325475     0.56   0.581    -.4860287    .8496104
         27  |   .2071646   .3373787     0.61   0.544    -.4850793    .8994084
         28  |   .2087696   .3384247     0.62   0.542    -.4856205    .9031597
         29  |     .23338   .3131627     0.75   0.463    -.4091768    .8759369
         30  |   .0983244   .3391683     0.29   0.774    -.5975915    .7942403
         31  |   .4315627   .3384565     1.28   0.213    -.2628926    1.126018
         32  |   .2401542   .3340703     0.72   0.478    -.4453015      .92561
         33  |   .2477679   .3562175     0.70   0.493      -.48313    .9786659
         34  |   .2300846   .3788048     0.61   0.549    -.5471586    1.007328
         35  |   .5793082   .4169866     1.39   0.176    -.2762776    1.434894
         36  |    .213927   .4126411     0.52   0.608    -.6327426    1.060597
         37  |   .2958091   .5510963     0.54   0.596    -.8349471    1.426565
         38  |   .4800372   .5499557     0.87   0.390    -.6483787    1.608453
         39  |   .0554166   .5637992     0.10   0.922    -1.101404    1.212237
         40  |   .4381228   .5300462     0.83   0.416    -.6494421    1.525688
         41  |  -.4831794   .3261449    -1.48   0.150    -1.152374    .1860148
         42  |   -.441988   .3247275    -1.36   0.185    -1.108274    .2242979
         43  |   .0789911    .693667     0.11   0.910    -1.344296    1.502278
         44  |  -.4432825   .3331698    -1.33   0.194     -1.12689    .2403254
         45  |  -.4415731   .3313362    -1.33   0.194    -1.121419    .2382726
         46  |  -.5076897   .3312317    -1.53   0.137    -1.187321    .1719415
         47  |  -.4917069   .3349126    -1.47   0.154    -1.178891     .195477
         48  |  -.4442047   .3267504    -1.36   0.185    -1.114641    .2262318
         49  |  -.5109696   .3399764    -1.50   0.144    -1.208544    .1866043
         50  |  -.3012236   .3282873    -0.92   0.367    -.9748134    .3723663
             |
 birth_month |
          1  |  -.5688605   .3294651    -1.73   0.096    -1.244867     .107146
          2  |  -.5922903   .3272969    -1.81   0.081    -1.263848    .0792675
          3  |  -.5294971    .314459    -1.68   0.104    -1.174714    .1157195
          4  |  -.5706361   .3171159    -1.80   0.083    -1.221304    .0800321
          5  |  -.5264798   .3349894    -1.57   0.128    -1.213821    .1608617
          6  |  -.4874263   .3210027    -1.52   0.141    -1.146069    .1712169
          7  |  -.5419169   .3261829    -1.66   0.108    -1.211189    .1273551
          8  |  -.4913095   .3160339    -1.55   0.132    -1.139757    .1571384
          9  |  -.5325742   .3329626    -1.60   0.121    -1.215757    .1506087
         10  |  -.5564516   .3395917    -1.64   0.113    -1.253236     .140333
         11  |  -.5572048   .3184213    -1.75   0.091    -1.210551    .0961417
         12  |  -.5529765   .3306596    -1.67   0.106    -1.231434    .1254809
             |
        prov |
         12  |   .0253678   .1072947     0.24   0.815    -.1947828    .2455183
         13  |  -.0990429    .060191    -1.65   0.111    -.2225445    .0244588
         14  |  -.4015711   .1032533    -3.89   0.001    -.6134294   -.1897128
         15  |   .1935118   .0892101     2.17   0.039     .0104679    .3765558
         21  |   .0559203   .0141205     3.96   0.000     .0269474    .0848931
         22  |  -.0349533   .1158811    -0.30   0.765    -.2727216     .202815
         23  |   .1959468   .0859662     2.28   0.031     .0195587    .3723348
         31  |   .0498613     .04144     1.20   0.239    -.0351665    .1348891
         32  |  -.0462317   .0451398    -1.02   0.315    -.1388509    .0463874
         33  |  -.2660254   .0627398    -4.24   0.000    -.3947569    -.137294
         34  |  -.1528692   .1115217    -1.37   0.182    -.3816928    .0759544
         35  |  -.0632247   .0472869    -1.34   0.192    -.1602494    .0337999
         36  |  -.2091642   .0747554    -2.80   0.009    -.3625497   -.0557788
         37  |   .0137897   .1086192     0.13   0.900    -.2090785    .2366578
         41  |   .0795895    .075132     1.06   0.299    -.0745686    .2337476
         42  |   .1001913   .0543261     1.84   0.076    -.0112767    .2116594
         43  |  -.0794338   .0579198    -1.37   0.182    -.1982753    .0394078
         44  |  -.1296827   .0605183    -2.14   0.041     -.253856   -.0055095
         45  |  -.2785719   .0273539   -10.18   0.000    -.3346975   -.2224463
         51  |  -.0958804    .079456    -1.21   0.238    -.2589106    .0671499
         52  |  -.3855478    .075713    -5.09   0.000     -.540898   -.2301976
         53  |  -.0503641   .0599667    -0.84   0.408    -.1734056    .0726775
         61  |  -.2485779   .0806915    -3.08   0.005    -.4141431   -.0830127
         62  |  -.0856816   .0884714    -0.97   0.341      -.26721    .0958468
         63  |  -.4221971   .0873386    -4.83   0.000     -.601401   -.2429931
         64  |   .1426506   .0531392     2.68   0.012      .033618    .2516831
         65  |  -.1209833     .04467    -2.71   0.012    -.2126387    -.029328
             |
        cell |
          2  |  -.2327853   .1678996    -1.39   0.177    -.5772867    .1117162
          3  |  -.3392136   .1488742    -2.28   0.031    -.6446783   -.0337489
          4  |  -.2958182    .148791    -1.99   0.057     -.601112    .0094757
          5  |  -.2818848   .1443222    -1.95   0.061    -.5780094    .0142399
          6  |  -.2805496    .142169    -1.97   0.059    -.5722564    .0111571
          7  |  -.3220341    .128216    -2.51   0.018    -.5851117   -.0589565
          8  |  -.2858908   .1384919    -2.06   0.049    -.5700528   -.0017289
          9  |   -.281489   .1438241    -1.96   0.061    -.5765916    .0136136
         10  |  -.2215045   .1620797    -1.37   0.183    -.5540645    .1110556
         11  |  -.3746382   .1421634    -2.64   0.014    -.6663333    -.082943
         12  |  -.3262237   .1610225    -2.03   0.053    -.6566147    .0041672
         13  |  -.2647483   .1476361    -1.79   0.084    -.5676726    .0381759
         14  |   -.345082   .1586933    -2.17   0.039    -.6706938   -.0194701
         15  |  -.3263482   .1676646    -1.95   0.062    -.6703676    .0176712
         16  |  -.4397369   .1572696    -2.80   0.009    -.7624274   -.1170464
         17  |  -.3536714     .21064    -1.68   0.105    -.7858691    .0785262
         18  |  -.4347269   .1772935    -2.45   0.021    -.7985032   -.0709506
         19  |   .3553798   .2272803     1.56   0.130    -.1109608    .8217204
         20  |   .3608087   .3070493     1.18   0.250    -.2692045     .990822
         21  |   .1871445   .2698605     0.69   0.494    -.3665635    .7408525
         22  |   .1834949   .2345465     0.78   0.441    -.2977548    .6647446
         23  |   .2619572   .2530776     1.04   0.310    -.2573152    .7812297
         24  |   .1802643   .2347876     0.77   0.449      -.30148    .6620086
         25  |   .1798259   .2386326     0.75   0.458    -.3098076    .6694595
         26  |   .1814951   .2420807     0.75   0.460    -.3152135    .6782037
         27  |   .2116699     .21042     1.01   0.323    -.2200762     .643416
         28  |   .1873012   .1894798     0.99   0.332    -.2014792    .5760817
         29  |   .2229949   .2235171     1.00   0.327    -.2356243    .6816141
         30  |   .1868651   .2175303     0.86   0.398    -.2594702    .6332003
         31  |   .2274788   .2101261     1.08   0.289    -.2036644    .6586219
         32  |   .3159746   .2209602     1.43   0.164    -.1373982    .7693474
         33  |   .3621658   .2315642     1.56   0.129    -.1129647    .8372963
         34  |   .4238369    .221493     1.91   0.066    -.0306292     .878303
         35  |   .3758879   .2065275     1.82   0.080    -.0478714    .7996473
         36  |   .3205254    .232565     1.38   0.179    -.1566586    .7977094
         37  |    .324077   .2488204     1.30   0.204    -.1864604    .8346143
         38  |   .2627796   .2521286     1.04   0.307    -.2545455    .7801048
         39  |   .2482525   .2110967     1.18   0.250    -.1848822    .6813871
         40  |   .3098299   .2200712     1.41   0.171    -.1417189    .7613788
         41  |   .3122688   .2219603     1.41   0.171     -.143156    .7676937
         42  |   .3358823   .2245678     1.50   0.146    -.1248927    .7966573
         43  |   .3517941   .1970215     1.79   0.085    -.0524607    .7560489
         44  |   .4168518   .2124393     1.96   0.060    -.0190376    .8527412
         45  |   .4495458   .2088762     2.15   0.040     .0209672    .8781244
         46  |   .3754908   .1984591     1.89   0.069    -.0317136    .7826952
         47  |   .3937945   .1726302     2.28   0.031     .0395867    .7480024
         48  |   .3084131   .1666386     1.85   0.075     -.033501    .6503273
         49  |   .3299481   .1760104     1.87   0.072    -.0311954    .6910915
         50  |   .1834525   .1365235     1.34   0.190    -.0966705    .4635755
         51  |   .1346415   .1304386     1.03   0.311    -.1329963    .4022794
         52  |   .1122481   .1390922     0.81   0.427    -.1731455    .3976416
         53  |   .0624265   .1388234     0.45   0.657    -.2224156    .3472686
         54  |   .1287447   .1367906     0.94   0.355    -.1519265    .4094158
         55  |   .0467851   .1253857     0.37   0.712    -.2104851    .3040552
         56  |   .0739734   .1279792     0.58   0.568    -.1886183    .3365651
         57  |  -.0956606   .2681604    -0.36   0.724    -.6458804    .4545592
         58  |   .2744581   .2085692     1.32   0.199    -.1534906    .7024068
         59  |   .1508791   .1828665     0.83   0.417     -.224332    .5260901
         60  |   .3821466   .2522473     1.51   0.141     -.135422    .8997153
         61  |  -.0301623   .1828228    -0.16   0.870    -.4052838    .3449592
         62  |   .0984803   .1938681     0.51   0.616    -.2993042    .4962647
         63  |   .0935002   .1753839     0.53   0.598    -.2663579    .4533582
         64  |   .0675613   .1841454     0.37   0.717    -.3102737    .4453964
         65  |   .2288115   .1432367     1.60   0.122    -.0650859    .5227089
         66  |   .0588609   .1997244     0.29   0.770    -.3509397    .4686614
         67  |   .1671585   .1498905     1.12   0.275    -.1403915    .4747085
         68  |  -.0788626     .17181    -0.46   0.650    -.4313877    .2736625
         69  |   .0061515   .1589129     0.04   0.969    -.3199108    .3322138
         70  |   .0627895   .1474027     0.43   0.674    -.2396558    .3652349
         71  |          0  (omitted)
             |
   prov2Xyob |   .0069523   .0066186     1.05   0.303    -.0066279    .0205324
   prov3Xyob |   .0172612   .0032394     5.33   0.000     .0106146    .0239078
   prov4Xyob |   .0295554   .0059127     5.00   0.000     .0174236    .0416873
   prov5Xyob |   .0012218   .0053228     0.23   0.820    -.0096996    .0121432
   prov6Xyob |   -.000409   .0006608    -0.62   0.541    -.0017648    .0009469
   prov7Xyob |   .0126438   .0074065     1.71   0.099    -.0025532    .0278408
   prov8Xyob |    .004425   .0053612     0.83   0.416    -.0065752    .0154253
   prov9Xyob |   .0033091    .003427     0.97   0.343    -.0037226    .0103408
  prov10Xyob |   .0123762   .0027666     4.47   0.000     .0066997    .0180528
  prov11Xyob |   .0163383   .0038359     4.26   0.000     .0084676    .0242089
  prov12Xyob |   .0196845    .007171     2.75   0.011     .0049709     .034398
  prov13Xyob |   .0098417   .0025881     3.80   0.001     .0045312    .0151521
  prov14Xyob |   .0137885   .0046087     2.99   0.006     .0043323    .0232446
  prov15Xyob |   .0207766   .0060908     3.41   0.002     .0082794    .0332738
  prov16Xyob |   .0202068   .0045666     4.42   0.000     .0108369    .0295767
  prov17Xyob |   .0013386   .0030991     0.43   0.669    -.0050203    .0076974
  prov18Xyob |   .0064144   .0040399     1.59   0.124    -.0018748    .0147036
  prov19Xyob |   .0157606    .002854     5.52   0.000     .0099046    .0216166
  prov20Xyob |   .0194216   .0009195    21.12   0.000     .0175348    .0213083
  prov21Xyob |   .0076769   .0052058     1.47   0.152    -.0030044    .0183583
  prov22Xyob |   .0285863   .0043016     6.65   0.000     .0197601    .0374125
  prov23Xyob |   .0045038   .0038017     1.18   0.246    -.0032965    .0123042
  prov24Xyob |    .020147   .0051071     3.94   0.001     .0096682    .0306259
  prov25Xyob |   .0168221   .0050826     3.31   0.003     .0063934    .0272508
  prov26Xyob |   .0246977   .0056384     4.38   0.000     .0131286    .0362668
  prov27Xyob |   .0017002   .0022173     0.77   0.450    -.0028493    .0062496
  prov28Xyob |   .0128352   .0023004     5.58   0.000     .0081151    .0175553
       _cons |   .5181056   .3701089     1.40   0.173    -.2412952    1.277506
------------------------------------------------------------------------------

. outreg2 using "table1_2.xls", keep(fine_e) append dec(3)
table1_2.xls
dir : seeout

. reg twins order*Xfine_e i.order $control_1 [aw = weight] if h_fm_han == 1 & rural == 0, cluster(cluster_id)
(sum of wgt is   1.7749e+06)
note: rural omitted because of collinearity
note: h_fm_han omitted because of collinearity
note: 71.cell omitted because of collinearity

Linear regression                                      Number of obs = 1422621
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.0009
                                                       Root MSE      =  8.1066

                             (Std. Err. adjusted for 28 clusters in cluster_id)
-------------------------------------------------------------------------------
              |               Robust
        twins |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
order1Xfine_e |     .05477   .0441421     1.24   0.225    -.0358021     .145342
order2Xfine_e |    .092063   .0574925     1.60   0.121    -.0259018    .2100278
order3Xfine_e |   .0207509   .0608387     0.34   0.736    -.1040797    .1455815
              |
        order |
           2  |     .16563   .0519931     3.19   0.004     .0589489     .272311
           3  |     .18071   .0556368     3.25   0.003     .0665528    .2948673
              |
        rural |          0  (omitted)
     h_fm_han |          0  (omitted)
              |
      h_m_edu |
           2  |   .0370951   .0326538     1.14   0.266    -.0299051    .1040952
           3  |   .0170081   .0421144     0.40   0.690    -.0694036    .1034198
           4  |  -.0629816   .0386538    -1.63   0.115    -.1422927    .0163295
              |
  m_birth_age |
          17  |   .0516975   .3117648     0.17   0.870     -.587991     .691386
          18  |  -.0591715   .3206017    -0.18   0.855    -.7169919     .598649
          19  |  -.0908671   .3296176    -0.28   0.785    -.7671866    .5854525
          20  |  -.0051946   .3195597    -0.02   0.987     -.660877    .6504878
          21  |   .0255167   .3206774     0.08   0.937     -.632459    .6834923
          22  |   .0780987   .3220022     0.24   0.810    -.5825954    .7387927
          23  |   .0631469   .3258036     0.19   0.848    -.6053469    .7316408
          24  |   .0536358   .3254645     0.16   0.870    -.6141622    .7214339
          25  |   .0942346   .3327829     0.28   0.779    -.5885795    .7770487
          26  |   .1828467   .3247766     0.56   0.578    -.4835398    .8492331
          27  |   .2083294   .3363482     0.62   0.541    -.4818002     .898459
          28  |   .2100951   .3371846     0.62   0.538    -.4817506    .9019408
          29  |   .2345894   .3124043     0.75   0.459    -.4064112      .87559
          30  |    .099664   .3376934     0.30   0.770    -.5932257    .7925537
          31  |   .4330054   .3366705     1.29   0.209    -.2577853    1.123796
          32  |   .2419103   .3324378     0.73   0.473    -.4401958    .9240164
          33  |    .249138   .3549822     0.70   0.489    -.4792254    .9775014
          34  |   .2319741   .3781688     0.61   0.545    -.5439642    1.007912
          35  |   .5805717   .4156023     1.40   0.174    -.2721738    1.433317
          36  |   .2163912   .4113375     0.53   0.603    -.6276038    1.060386
          37  |   .2971781   .5518249     0.54   0.595    -.8350731    1.429429
          38  |   .4808071   .5506995     0.87   0.390    -.6491349    1.610749
          39  |   .0566506    .563313     0.10   0.921    -1.099172    1.212473
          40  |   .4393959   .5296698     0.83   0.414    -.6473967    1.526189
          41  |  -.4809924   .3248136    -1.48   0.150    -1.147455    .1854701
          42  |  -.4419051   .3242284    -1.36   0.184    -1.107167    .2233566
          43  |   .0822546   .6934154     0.12   0.906    -1.340516    1.505025
          44  |  -.4424261   .3324127    -1.33   0.194    -1.124481    .2396285
          45  |  -.4394276    .330445    -1.33   0.195    -1.117445    .2385894
          46  |  -.4945498   .3306295    -1.50   0.146    -1.172946     .183846
          47  |  -.4911973   .3331422    -1.47   0.152    -1.174749     .192354
          48  |  -.4468079   .3284394    -1.36   0.185     -1.12071     .227094
          49  |  -.5135992   .3426773    -1.50   0.146    -1.216715    .1895165
          50  |  -.3052995   .3325717    -0.92   0.367    -.9876803    .3770813
              |
  birth_month |
           1  |  -.5551176    .358319    -1.55   0.133    -1.290327    .1800923
           2  |  -.5785688   .3518644    -1.64   0.112    -1.300535    .1433974
           3  |  -.5156802   .3361034    -1.53   0.137    -1.205307     .173947
           4  |  -.5569777   .3418729    -1.63   0.115    -1.258443    .1444875
           5  |  -.5127249   .3596176    -1.43   0.165    -1.250599    .2251493
           6  |  -.4738751   .3434654    -1.38   0.179    -1.178608    .2308576
           7  |  -.5282707   .3531314    -1.50   0.146    -1.252837    .1962951
           8  |  -.4775451   .3386569    -1.41   0.170    -1.172412    .2173213
           9  |  -.5186634   .3585734    -1.45   0.160    -1.254395    .2170685
          10  |  -.5426109   .3694584    -1.47   0.153    -1.300677    .2154552
          11  |  -.5435798   .3423602    -1.59   0.124    -1.246045    .1588852
          12  |  -.5393604   .3559715    -1.52   0.141    -1.269754    .1910328
              |
         prov |
          12  |   .0301915   .1109045     0.27   0.788    -.1973658    .2577488
          13  |   -.091302   .0656907    -1.39   0.176    -.2260883    .0434843
          14  |  -.3966548   .1070006    -3.71   0.001    -.6162018   -.1771078
          15  |   .1967493   .0924226     2.13   0.043     .0071138    .3863849
          21  |   .0588045   .0151161     3.89   0.001     .0277888    .0898201
          22  |  -.0302322   .1207698    -0.25   0.804    -.2780314    .2175669
          23  |   .1992202   .0896754     2.22   0.035     .0152215    .3832189
          31  |   .0491764   .0414601     1.19   0.246    -.0358928    .1342456
          32  |  -.0433473   .0468386    -0.93   0.363    -.1394522    .0527577
          33  |  -.2594235   .0674169    -3.85   0.001    -.3977515   -.1210955
          34  |  -.1501419   .1162459    -1.29   0.207    -.3886587    .0883749
          35  |  -.0560887    .054249    -1.03   0.310    -.1673985    .0552211
          36  |  -.2051685   .0810302    -2.53   0.017    -.3714289   -.0389082
          37  |   .0178341    .112361     0.16   0.875    -.2127116    .2483798
          41  |   .0842684   .0808899     1.04   0.307     -.081704    .2502408
          42  |   .1057746   .0579453     1.83   0.079    -.0131194    .2246685
          43  |  -.0739665   .0620575    -1.19   0.244    -.2012979    .0533649
          44  |  -.1242305   .0768242    -1.62   0.117    -.2818609    .0333998
          45  |  -.2714162   .0380697    -7.13   0.000    -.3495288   -.1933037
          51  |  -.0927398   .0831243    -1.12   0.274    -.2632968    .0778171
          52  |  -.3805851   .0833666    -4.57   0.000    -.5516392   -.2095311
          53  |  -.0404652   .0699534    -0.58   0.568    -.1839977    .1030674
          61  |  -.2427606   .0857022    -2.83   0.009    -.4186069   -.0669143
          62  |  -.0811877   .0938053    -0.87   0.394    -.2736603     .111285
          63  |  -.4194435   .0900809    -4.66   0.000    -.6042741   -.2346128
          64  |   .1462063   .0564418     2.59   0.015     .0303972    .2620153
          65  |  -.1206611   .0479472    -2.52   0.018    -.2190406   -.0222816
              |
         cell |
           2  |  -.2280279   .1696863    -1.34   0.190    -.5761954    .1201396
           3  |  -.3247519   .1496947    -2.17   0.039    -.6319001   -.0176037
           4  |  -.2795512   .1528496    -1.83   0.078    -.5931728    .0340703
           5  |  -.2690988   .1470415    -1.83   0.078    -.5708031    .0326056
           6  |  -.2696022   .1488176    -1.81   0.081    -.5749506    .0357462
           7  |  -.3109554   .1354511    -2.30   0.030     -.588878   -.0330327
           8  |  -.2745064   .1495732    -1.84   0.078    -.5814052    .0323924
           9  |  -.2713206    .148832    -1.82   0.079    -.5766986    .0340573
          10  |  -.2126207   .1723338    -1.23   0.228    -.5662205     .140979
          11  |  -.3671165   .1606375    -2.29   0.030    -.6967173   -.0375156
          12  |  -.3183781   .1741718    -1.83   0.079     -.675749    .0389929
          13  |  -.2558471   .1594947    -1.60   0.120    -.5831032     .071409
          14  |  -.3351547   .1732436    -1.93   0.064    -.6906213    .0203119
          15  |  -.3151947   .1864051    -1.69   0.102    -.6976664     .067277
          16  |   -.428614   .1586607    -2.70   0.012    -.7541589    -.103069
          17  |  -.3439604   .2191521    -1.57   0.128    -.7936233    .1057025
          18  |  -.4247476   .1844196    -2.30   0.029    -.8031455   -.0463498
          19  |   .3432936   .2535421     1.35   0.187    -.1769319    .8635191
          20  |   .3499558   .3203783     1.09   0.284    -.3074063    1.007318
          21  |   .1841328   .2858167     0.64   0.525    -.4023145    .7705802
          22  |   .1857415     .24935     0.74   0.463    -.3258824    .6973653
          23  |   .2652098   .2632636     1.01   0.323    -.2749624     .805382
          24  |   .1827218   .2432584     0.75   0.459    -.3164032    .6818467
          25  |   .1805695   .2460756     0.73   0.469     -.324336    .6854749
          26  |   .1817771   .2477562     0.73   0.469    -.3265767    .6901308
          27  |    .208776   .2218901     0.94   0.355     -.246505     .664057
          28  |   .1833552   .2030493     0.90   0.375    -.2332675    .5999778
          29  |   .2193336   .2336956     0.94   0.356    -.2601701    .6988372
          30  |    .183381   .2293366     0.80   0.431    -.2871788    .6539408
          31  |   .2244428   .2207425     1.02   0.318    -.2284834     .677369
          32  |   .3133923   .2304015     1.36   0.185    -.1593526    .7861372
          33  |   .3600628   .2382812     1.51   0.142    -.1288499    .8489755
          34  |   .4219823   .2279193     1.85   0.075    -.0456693     .889634
          35  |   .3741682   .2141023     1.75   0.092    -.0651335    .8134698
          36  |   .3192612    .238635     1.34   0.192    -.1703774    .8088998
          37  |   .3229399   .2589364     1.25   0.223    -.2083537    .8542334
          38  |   .2585909   .2678653     0.97   0.343    -.2910232    .8082051
          39  |   .2438135   .2201881     1.11   0.278    -.2079751    .6956022
          40  |   .3057816   .2312941     1.32   0.197    -.1687947    .7803578
          41  |   .3090688   .2300336     1.34   0.190    -.1629213    .7810588
          42  |   .3332394   .2328268     1.43   0.164    -.1444818    .8109606
          43  |   .3496024   .2060569     1.70   0.101    -.0731913    .7723962
          44  |    .415123   .2191807     1.89   0.069    -.0345987    .8648447
          45  |   .4482251   .2148721     2.09   0.047     .0073441    .8891062
          46  |   .3742801   .2038672     1.84   0.077    -.0440209    .7925811
          47  |   .3925692   .1786912     2.20   0.037      .025925    .7592133
          48  |   .3070534   .1740845     1.76   0.089    -.0501385    .6642453
          49  |   .3289073   .1864132     1.76   0.089     -.053581    .7113956
          50  |    .182987   .1411803     1.30   0.206     -.106691    .4726651
          51  |   .1344892   .1369289     0.98   0.335    -.1464658    .4154442
          52  |   .1124049   .1427351     0.79   0.438    -.1804633     .405273
          53  |   .0627859   .1433601     0.44   0.665    -.2313648    .3569366
          54  |   .1288825   .1399138     0.92   0.365    -.1581969    .4159618
          55  |   .0469925   .1267283     0.37   0.714    -.2130326    .3070175
          56  |   .0740679   .1283428     0.58   0.569    -.1892698    .3374056
          57  |  -.0990583    .280822    -0.35   0.727    -.6752575    .4771409
          58  |   .2714528   .2147717     1.26   0.217    -.1692224     .712128
          59  |   .1483081   .1902399     0.78   0.442    -.2420319    .5386482
          60  |   .3804093    .255044     1.49   0.147    -.1428977    .9037163
          61  |  -.0315334   .1896497    -0.17   0.869    -.4206626    .3575957
          62  |   .0972289   .2019183     0.48   0.634    -.3170733    .5115311
          63  |   .0922169   .1809196     0.51   0.614    -.2789995    .4634333
          64  |   .0663472   .1909819     0.35   0.731    -.3255153    .4582096
          65  |   .2276015   .1430159     1.59   0.123    -.0658428    .5210458
          66  |   .0575046   .2078588     0.28   0.784    -.3689865    .4839958
          67  |    .168011   .1532287     1.10   0.283    -.1463882    .4824103
          68  |  -.0790331   .1779596    -0.44   0.661    -.4441761    .2861098
          69  |   .0055247    .161183     0.03   0.973    -.3251955    .3362448
          70  |   .0623697   .1484037     0.42   0.678    -.2421296    .3668691
          71  |          0  (omitted)
              |
    prov2Xyob |   .0066338   .0068565     0.97   0.342    -.0074346    .0207021
    prov3Xyob |   .0167839    .003761     4.46   0.000     .0090669    .0245008
    prov4Xyob |    .029245   .0062345     4.69   0.000     .0164529    .0420371
    prov5Xyob |   .0009849   .0055683     0.18   0.861    -.0104402    .0124101
    prov6Xyob |  -.0005859   .0008477    -0.69   0.495    -.0023251    .0011534
    prov7Xyob |   .0123048   .0077217     1.59   0.123    -.0035389    .0281484
    prov8Xyob |   .0041774   .0056235     0.74   0.464     -.007361    .0157159
    prov9Xyob |   .0031955   .0035125     0.91   0.371    -.0040116    .0104026
   prov10Xyob |   .0121816   .0029391     4.14   0.000     .0061511    .0182121
   prov11Xyob |   .0159309     .00419     3.80   0.001     .0073338     .024528
   prov12Xyob |    .019505   .0074641     2.61   0.014       .00419    .0348199
   prov13Xyob |   .0094089   .0032464     2.90   0.007     .0027478      .01607
   prov14Xyob |    .013482   .0050678     2.66   0.013     .0030838    .0238802
   prov15Xyob |   .0205021   .0064009     3.20   0.003     .0073686    .0336357
   prov16Xyob |   .0198701   .0049926     3.98   0.000     .0096261     .030114
   prov17Xyob |   .0009796   .0034747     0.28   0.780    -.0061499    .0081091
   prov18Xyob |    .006096    .004381     1.39   0.175    -.0028931    .0150851
   prov19Xyob |   .0154032    .004241     3.63   0.001     .0067013    .0241051
   prov20Xyob |   .0189594   .0025107     7.55   0.000     .0138078     .024111
   prov21Xyob |   .0074381   .0054538     1.36   0.184    -.0037522    .0186283
   prov22Xyob |    .028249   .0048799     5.79   0.000     .0182363    .0382617
   prov23Xyob |   .0038926    .004458     0.87   0.390    -.0052545    .0130396
   prov24Xyob |   .0197925   .0054696     3.62   0.001     .0085699    .0310151
   prov25Xyob |   .0165076   .0054565     3.03   0.005     .0053119    .0277033
   prov26Xyob |   .0244617   .0058736     4.16   0.000     .0124101    .0365133
   prov27Xyob |   .0013611   .0026701     0.51   0.614    -.0041175    .0068397
   prov28Xyob |   .0126917   .0025141     5.05   0.000     .0075331    .0178503
        _cons |   .5133263   .3659199     1.40   0.172    -.2374794    1.264132
-------------------------------------------------------------------------------

. outreg2 using "table1_2.xls", keep(order1Xfine_e order2Xfine_e order3Xfine_e) append dec(3)
table1_2.xls
dir : seeout

. reg twins fine_e i.order $control_1 [aw = weight] if h_fm_han == 1 & rural == 1, cluster(cluster_id)
(sum of wgt is   4.6246e+06)
note: rural omitted because of collinearity
note: h_fm_han omitted because of collinearity
note: 71.cell omitted because of collinearity

Linear regression                                      Number of obs = 4231573
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.0013
                                                       Root MSE      =  7.4539

                            (Std. Err. adjusted for 28 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
       twins |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      fine_e |   .0851354   .0419258     2.03   0.052    -.0008893      .17116
             |
       order |
          2  |   .2263726   .0330279     6.85   0.000      .158605    .2941402
          3  |   .2141534   .0219333     9.76   0.000       .16915    .2591568
             |
       rural |          0  (omitted)
    h_fm_han |          0  (omitted)
             |
     h_m_edu |
          2  |   .0400045   .0124219     3.22   0.003      .014517    .0654921
          3  |   .0677502   .0192893     3.51   0.002     .0281718    .1073286
          4  |   .1682813   .0325651     5.17   0.000     .1014632    .2350994
             |
 m_birth_age |
         17  |   .0027138   .0872058     0.03   0.975    -.1762177    .1816453
         18  |   .0667251   .0679909     0.98   0.335    -.0727807    .2062309
         19  |   .0503649   .0772991     0.65   0.520    -.1082397    .2089696
         20  |   .0709788   .0755044     0.94   0.356    -.0839435    .2259011
         21  |   .1004749    .073142     1.37   0.181    -.0496001    .2505499
         22  |   .1381277   .0684166     2.02   0.054    -.0022517     .278507
         23  |     .18679   .0639877     2.92   0.007      .055498     .318082
         24  |   .2032622   .0715767     2.84   0.008      .056399    .3501254
         25  |   .2467273   .0629918     3.92   0.001     .1174787    .3759758
         26  |    .271509   .0703599     3.86   0.001     .1271424    .4158755
         27  |   .2893456   .0651029     4.44   0.000     .1557655    .4229257
         28  |   .3365938   .0778122     4.33   0.000     .1769363    .4962512
         29  |   .3862962   .0642711     6.01   0.000     .2544228    .5181695
         30  |   .4569232   .0875608     5.22   0.000     .2772632    .6365833
         31  |   .4920751    .108379     4.54   0.000     .2696998    .7144504
         32  |   .4454388   .1419625     3.14   0.004     .1541558    .7367218
         33  |   .3367744   .1361019     2.47   0.020     .0575163    .6160324
         34  |   .7119997   .1716588     4.15   0.000      .359785    1.064214
         35  |   .7400144   .2751383     2.69   0.012     .1754773    1.304552
         36  |   .1262759   .1380117     0.91   0.368    -.1569007    .4094525
         37  |   .2817937   .3645453     0.77   0.446    -.4661915    1.029779
         38  |   .2319131   .1692041     1.37   0.182     -.115265    .5790912
         39  |  -.0540539   .1841662    -0.29   0.771    -.4319317    .3238239
         40  |   .8362541   .8716503     0.96   0.346    -.9522246    2.624733
         41  |   .3391082   .3065829     1.11   0.278    -.2899479    .9681642
         42  |   1.006234   .5529765     1.82   0.080      -.12838    2.140848
         43  |   .0776331   .3102811     0.25   0.804     -.559011    .7142773
         44  |   .1170219   .3978021     0.29   0.771    -.6992005    .9332443
         45  |   .2823934   .5428264     0.52   0.607    -.8313944    1.396181
         46  |  -.3272627   .0758787    -4.31   0.000     -.482953   -.1715723
         47  |  -.2946777   .0660954    -4.46   0.000    -.4302942   -.1590612
         48  |  -.3613787   .0760389    -4.75   0.000    -.5173976   -.2053599
         49  |   1.579618   1.899882     0.83   0.413    -2.318617    5.477853
         50  |  -.2488006   .0775739    -3.21   0.003     -.407969   -.0896322
             |
 birth_month |
          1  |  -.5930102   .2945348    -2.01   0.054    -1.197346    .0113252
          2  |  -.5789337   .2868339    -2.02   0.054    -1.167468    .0096009
          3  |  -.5640815   .2852524    -1.98   0.058    -1.149371    .0212081
          4  |  -.5512994    .285979    -1.93   0.064     -1.13808    .0354811
          5  |  -.5454087    .284105    -1.92   0.066    -1.128344    .0375265
          6  |  -.5144909   .2856155    -1.80   0.083    -1.100525    .0715436
          7  |  -.5302438   .2806281    -1.89   0.070    -1.106045    .0455576
          8  |  -.5488215    .284668    -1.93   0.064    -1.132912     .035269
          9  |  -.5614767   .2856538    -1.97   0.060     -1.14759    .0246366
         10  |  -.5633914   .2744409    -2.05   0.050    -1.126498   -.0002853
         11  |  -.5995542   .2889883    -2.07   0.048    -1.192509   -.0065991
         12  |  -.5709636   .2824821    -2.02   0.053    -1.150569    .0086418
             |
        prov |
         12  |  -.2717177   .0856216    -3.17   0.004    -.4473987   -.0960366
         13  |   -.314533   .0329082    -9.56   0.000     -.382055   -.2470111
         14  |  -.2917189   .0679419    -4.29   0.000    -.4311243   -.1523135
         15  |  -.1298522   .0531796    -2.44   0.021    -.2389677   -.0207366
         21  |  -.1592318   .0072659   -21.91   0.000    -.1741403   -.1443233
         22  |  -.2312004   .0758106    -3.05   0.005     -.386751   -.0756498
         23  |  -.0926587   .0544233    -1.70   0.100    -.2043261    .0190086
         31  |  -.2098495    .040595    -5.17   0.000    -.2931435   -.1265555
         32  |  -.3727799   .0284952   -13.08   0.000    -.4312472   -.3143127
         33  |  -.1668579    .037276    -4.48   0.000     -.243342   -.0903738
         34  |  -.3780586   .0699046    -5.41   0.000     -.521491   -.2346261
         35  |  -.2767789   .0277221    -9.98   0.000      -.33366   -.2198977
         36  |   -.335008   .0504855    -6.64   0.000    -.4385956   -.2314204
         37  |  -.2531723   .0628896    -4.03   0.000     -.382211   -.1241336
         41  |  -.3735553   .0472832    -7.90   0.000    -.4705724   -.2765382
         42  |  -.0065015   .0318711    -0.20   0.840    -.0718955    .0588925
         43  |  -.3038876   .0370643    -8.20   0.000    -.3799374   -.2278379
         44  |  -.3263513   .0260818   -12.51   0.000    -.3798668   -.2728358
         45  |  -.2142532   .0109081   -19.64   0.000    -.2366348   -.1918717
         51  |  -.4583785   .0496208    -9.24   0.000    -.5601919    -.356565
         52  |   -.335187   .0505104    -6.64   0.000    -.4388257   -.2315482
         53  |  -.2709384   .0451764    -6.00   0.000    -.3636326   -.1782441
         61  |  -.3489141   .0525712    -6.64   0.000    -.4567813    -.241047
         62  |  -.3373862   .0580147    -5.82   0.000    -.4564225   -.2183498
         63  |  -.5136737   .0711159    -7.22   0.000    -.6595915    -.367756
         64  |  -.2546674   .0266419    -9.56   0.000     -.309332   -.2000028
         65  |  -.1146226   .0201288    -5.69   0.000    -.1559235   -.0733217
             |
        cell |
          2  |  -.0694291   .0580004    -1.20   0.242    -.1884361    .0495778
          3  |  -.2110014   .0406882    -5.19   0.000    -.2944866   -.1275162
          4  |   -.191704   .0592608    -3.23   0.003    -.3132972   -.0701107
          5  |  -.1651019   .0432925    -3.81   0.001    -.2539308   -.0762731
          6  |  -.1402643   .0445869    -3.15   0.004    -.2317491   -.0487795
          7  |  -.2051678   .0484773    -4.23   0.000     -.304635   -.1057005
          8  |  -.2280941   .0483224    -4.72   0.000    -.3272434   -.1289448
          9  |  -.2387537   .0546716    -4.37   0.000    -.3509306   -.1265767
         10  |  -.2485165   .0522225    -4.76   0.000    -.3556682   -.1413648
         11  |  -.2979902   .0650844    -4.58   0.000    -.4315325    -.164448
         12  |  -.2349957   .0522273    -4.50   0.000    -.3421573   -.1278341
         13  |  -.2825111   .0571519    -4.94   0.000    -.3997772   -.1652451
         14  |  -.2743244   .0689619    -3.98   0.000    -.4158225   -.1328263
         15  |    -.28516   .0735979    -3.87   0.001    -.4361705   -.1341495
         16  |  -.3145871   .0791784    -3.97   0.000    -.4770477   -.1521265
         17  |    -.38867    .093163    -4.17   0.000    -.5798247   -.1975154
         18  |  -.3958462   .1004297    -3.94   0.001    -.6019109   -.1897814
         19  |   .4234288   .2904413     1.46   0.156    -.1725076    1.019365
         20  |    .311413   .2734385     1.14   0.265    -.2496365    .8724625
         21  |   .2992781       .282     1.06   0.298    -.2793381    .8778942
         22  |   .2193644   .2677147     0.82   0.420    -.3299407    .7686696
         23  |   .2076491   .2659859     0.78   0.442    -.3381089    .7534071
         24  |   .1967776   .2717188     0.72   0.475    -.3607433    .7542986
         25  |    .234831   .2569109     0.91   0.369    -.2923067    .7619686
         26  |   .2038137   .2579281     0.79   0.436    -.3254111    .7330385
         27  |   .1492333   .2427433     0.61   0.544    -.3488349    .6473014
         28  |   .1196917   .2098738     0.57   0.573    -.3109337    .5503172
         29  |   .1587722   .2233037     0.71   0.483    -.2994091    .6169535
         30  |   .1608371   .2244426     0.72   0.480    -.2996812    .6213554
         31  |   .2101252   .2248776     0.93   0.358    -.2512855    .6715358
         32  |   .2112958   .2300275     0.92   0.366    -.2606815    .6832732
         33  |    .229716   .2297637     1.00   0.326    -.2417201    .7011522
         34  |    .232039   .2322845     1.00   0.327    -.2445694    .7086475
         35  |   .2780126   .2400441     1.16   0.257    -.2145172    .7705424
         36  |    .255219   .2309933     1.10   0.279    -.2187401     .729178
         37  |   .3687189    .212395     1.74   0.094    -.0670796    .8045175
         38  |   .0411588   .2211916     0.19   0.854    -.4126889    .4950064
         39  |   .2132231   .2409135     0.89   0.384    -.2810905    .7075368
         40  |   .2358117   .2238011     1.05   0.301    -.2233901    .6950136
         41  |   .2304939   .2378111     0.97   0.341     -.257454    .7184419
         42  |   .2257507   .2347385     0.96   0.345     -.255893    .7073943
         43  |   .2187377   .2252073     0.97   0.340    -.2433495     .680825
         44  |   .2767848   .2250275     1.23   0.229    -.1849334     .738503
         45  |   .3292576   .2277504     1.45   0.160    -.1380477    .7965628
         46  |   .2559221   .2090966     1.22   0.232    -.1731088    .6849529
         47  |    .234367   .2034293     1.15   0.259    -.1830354    .6517694
         48  |   .2670956   .1953491     1.37   0.183    -.1337276    .6679188
         49  |   .2580521   .2066107     1.25   0.222     -.165878    .6819821
         50  |   .2531648   .1881091     1.35   0.190    -.1328032    .6391328
         51  |   .1833981   .1808961     1.01   0.320    -.1877701    .5545662
         52  |   .2185793   .1784902     1.22   0.231    -.1476524    .5848109
         53  |   .2329561   .1653661     1.41   0.170    -.1063471    .5722593
         54  |   .1366735   .1566938     0.87   0.391    -.1848356    .4581825
         55  |   .1735607   .1741617     1.00   0.328    -.1837895    .5309109
         56  |   .2343698   .1856007     1.26   0.217    -.1464513    .6151909
         57  |   .3643592   .3526339     1.03   0.311    -.3591858    1.087904
         58  |     .16246   .2330089     0.70   0.492    -.3156348    .6405548
         59  |   .2334247   .2414826     0.97   0.342    -.2620566     .728906
         60  |   .1560625   .2061631     0.76   0.456    -.2669493    .5790743
         61  |   .1193916   .1948704     0.61   0.545    -.2804493    .5192326
         62  |   .0769383    .219445     0.35   0.729    -.3733257    .5272023
         63  |     .14499    .177539     0.82   0.421    -.2192899    .5092699
         64  |   .0362855   .2149538     0.17   0.867    -.4047631    .4773342
         65  |   .0261601   .2157263     0.12   0.904    -.4164737     .468794
         66  |   .0862805   .2101981     0.41   0.685    -.3450104    .5175713
         67  |   .0459544    .173187     0.27   0.793    -.3093961    .4013049
         68  |   .2780363   .1827247     1.52   0.140    -.0968837    .6529564
         69  |  -.0320344   .1736912    -0.18   0.855    -.3884194    .3243505
         70  |  -.0158446   .1767039    -0.09   0.929     -.378411    .3467218
         71  |          0  (omitted)
             |
   prov2Xyob |   .0113728   .0051916     2.19   0.037     .0007205     .022025
   prov3Xyob |   .0183638    .001549    11.86   0.000     .0151856    .0215421
   prov4Xyob |   .0162525   .0041525     3.91   0.001     .0077322    .0247728
   prov5Xyob |   .0104157   .0031404     3.32   0.003     .0039721    .0168592
   prov6Xyob |   .0060867   .0006653     9.15   0.000     .0047217    .0074517
   prov7Xyob |    .018198   .0050316     3.62   0.001     .0078739    .0285221
   prov8Xyob |   .0069698   .0034074     2.05   0.051    -.0000215    .0139611
   prov9Xyob |   .0106544   .0029387     3.63   0.001     .0046246    .0166842
  prov10Xyob |   .0270088   .0015358    17.59   0.000     .0238575    .0301601
  prov11Xyob |   .0056791   .0022952     2.47   0.020     .0009697    .0103885
  prov12Xyob |   .0223616   .0048374     4.62   0.000     .0124361     .032287
  prov13Xyob |    .021593   .0015135    14.27   0.000     .0184876    .0246984
  prov14Xyob |   .0109843   .0028096     3.91   0.001     .0052195    .0167491
  prov15Xyob |   .0242192   .0038061     6.36   0.000     .0164098    .0320287
  prov16Xyob |    .029748   .0027731    10.73   0.000     .0240581    .0354379
  prov17Xyob |  -.0011914    .001627    -0.73   0.470    -.0045299     .002147
  prov18Xyob |    .009309   .0027049     3.44   0.002      .003759    .0148589
  prov19Xyob |   .0157659   .0012408    12.71   0.000     .0132201    .0183118
  prov20Xyob |   .0112607   .0003731    30.19   0.000     .0104953    .0120261
  prov21Xyob |   .0219735   .0032213     6.82   0.000      .015364    .0285829
  prov22Xyob |   .0152179   .0028418     5.35   0.000     .0093869    .0210489
  prov23Xyob |   .0057955     .00261     2.22   0.035     .0004403    .0111507
  prov24Xyob |   .0164831   .0034774     4.74   0.000     .0093482     .023618
  prov25Xyob |   .0173021   .0032268     5.36   0.000     .0106811     .023923
  prov26Xyob |   .0255514   .0045113     5.66   0.000      .016295    .0348078
  prov27Xyob |   .0085945    .001109     7.75   0.000     .0063189      .01087
  prov28Xyob |   .0131578   .0010213    12.88   0.000     .0110622    .0152534
       _cons |   .4499995   .0775953     5.80   0.000     .2907871    .6092118
------------------------------------------------------------------------------

. outreg2 using "table1_2.xls", keep(fine_e) append dec(3)
table1_2.xls
dir : seeout

. reg twins order*Xfine_e i.order $control_1 [aw = weight] if h_fm_han == 1 & rural == 1, cluster(cluster_id)
(sum of wgt is   4.6246e+06)
note: rural omitted because of collinearity
note: h_fm_han omitted because of collinearity
note: 71.cell omitted because of collinearity

Linear regression                                      Number of obs = 4231573
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.0013
                                                       Root MSE      =  7.4537

                             (Std. Err. adjusted for 28 clusters in cluster_id)
-------------------------------------------------------------------------------
              |               Robust
        twins |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
order1Xfine_e |   .0342967   .0408789     0.84   0.409    -.0495798    .1181732
order2Xfine_e |   .1689035   .0466622     3.62   0.001     .0731605    .2646465
order3Xfine_e |   .0885381   .0433507     2.04   0.051    -.0004103    .1774865
              |
        order |
           2  |   .1039574   .0221908     4.68   0.000     .0584255    .1494892
           3  |   .1632171   .0173292     9.42   0.000     .1276606    .1987736
              |
        rural |          0  (omitted)
     h_fm_han |          0  (omitted)
              |
      h_m_edu |
           2  |   .0391559   .0124321     3.15   0.004     .0136472    .0646645
           3  |   .0695508   .0190944     3.64   0.001     .0303724    .1087292
           4  |   .1709399    .032485     5.26   0.000     .1042863    .2375935
              |
  m_birth_age |
          17  |   .0033307   .0871202     0.04   0.970    -.1754251    .1820865
          18  |   .0680295   .0678506     1.00   0.325    -.0711883    .2072474
          19  |   .0515272   .0773223     0.67   0.511    -.1071251    .2101795
          20  |   .0712554   .0756532     0.94   0.355    -.0839722     .226483
          21  |   .1004732   .0734118     1.37   0.182    -.0501554    .2511019
          22  |   .1373469   .0686419     2.00   0.056    -.0034946    .2781885
          23  |   .1855959   .0642464     2.89   0.008     .0537733    .3174186
          24  |   .2019704    .071951     2.81   0.009     .0543392    .3496016
          25  |   .2452212   .0633539     3.87   0.001     .1152298    .3752126
          26  |   .2703858   .0706094     3.83   0.001     .1255073    .4152643
          27  |   .2893136     .06513     4.44   0.000     .1556778    .4229494
          28  |   .3371983   .0780153     4.32   0.000     .1771242    .4972724
          29  |   .3886993   .0642332     6.05   0.000     .2569037    .5204949
          30  |   .4594045   .0873714     5.26   0.000     .2801333    .6386758
          31  |   .4957632   .1082873     4.58   0.000     .2735761    .7179504
          32  |   .4501233   .1424241     3.16   0.004     .1578933    .7423533
          33  |   .3401386   .1358436     2.50   0.019     .0614106    .6188665
          34  |   .7162365   .1719627     4.17   0.000     .3633982    1.069075
          35  |   .7414364   .2751331     2.69   0.012     .1769098    1.305963
          36  |   .1314629   .1380213     0.95   0.349    -.1517335    .4146592
          37  |   .2833885    .364716     0.78   0.444    -.4649469    1.031724
          38  |   .2319722    .168918     1.37   0.181     -.114619    .5785633
          39  |  -.0489496   .1848536    -0.26   0.793    -.4282379    .3303386
          40  |   .8419172   .8722189     0.97   0.343     -.947728    2.631563
          41  |   .3405293   .3064795     1.11   0.276    -.2883148    .9693734
          42  |   1.005742   .5534704     1.82   0.080    -.1298857    2.141369
          43  |   .0769083   .3103653     0.25   0.806    -.5599086    .7137253
          44  |   .1230212   .3986169     0.31   0.760    -.6948731    .9409156
          45  |   .2808604   .5452509     0.52   0.611    -.8379021    1.399623
          46  |  -.3300782    .073866    -4.47   0.000    -.4816386   -.1785177
          47  |  -.3106524   .0673861    -4.61   0.000    -.4489172   -.1723876
          48  |  -.3619636   .0751161    -4.82   0.000     -.516089   -.2078382
          49  |   1.596922   1.899333     0.84   0.408    -2.300188    5.494032
          50  |  -.2310017   .0730081    -3.16   0.004    -.3808019   -.0812015
              |
  birth_month |
           1  |  -.4813384   .2875528    -1.67   0.106    -1.071348    .1086713
           2  |  -.4682177   .2802888    -1.67   0.106    -1.043323    .1068873
           3  |  -.4539837    .278796    -1.63   0.115    -1.026026    .1180584
           4  |  -.4414437   .2798299    -1.58   0.126    -1.015607    .1327199
           5  |  -.4360075   .2783094    -1.57   0.129    -1.007051    .1350362
           6  |  -.4050412    .278495    -1.45   0.157    -.9764657    .1663832
           7  |  -.4199756   .2737719    -1.53   0.137    -.9817092    .1417579
           8  |  -.4375802   .2783828    -1.57   0.128    -1.008775    .1336142
           9  |  -.4489121   .2794907    -1.61   0.120     -1.02238    .1245553
          10  |  -.4506145   .2679179    -1.68   0.104    -1.000337    .0991076
          11  |  -.4872333   .2823942    -1.73   0.096    -1.066658    .0921917
          12  |  -.4590421   .2761809    -1.66   0.108    -1.025718    .1076343
              |
         prov |
          12  |  -.2422837   .0839059    -2.89   0.008    -.4144444   -.0701229
          13  |  -.2832121    .032434    -8.73   0.000    -.3497611    -.216663
          14  |  -.2596434   .0668418    -3.88   0.001    -.3967913   -.1224954
          15  |  -.1027594   .0520947    -1.97   0.059    -.2096489    .0041302
          21  |  -.1420782   .0075163   -18.90   0.000    -.1575004   -.1266559
          22  |  -.1948634   .0739624    -2.63   0.014    -.3466217   -.0431052
          23  |  -.0657156    .053157    -1.24   0.227    -.1747847    .0433535
          31  |   -.197014   .0390574    -5.04   0.000    -.2771533   -.1168748
          32  |  -.3568823   .0276486   -12.91   0.000    -.4136124   -.3001521
          33  |  -.1400617   .0363823    -3.85   0.001     -.214712   -.0654114
          34  |  -.3454895   .0682779    -5.06   0.000    -.4855841   -.2053949
          35  |  -.2454091   .0274537    -8.94   0.000    -.3017393   -.1890788
          36  |  -.2999216   .0496196    -6.04   0.000    -.4017325   -.1981106
          37  |  -.2241467   .0614386    -3.65   0.001    -.3502083   -.0980851
          41  |  -.3413105   .0464494    -7.35   0.000    -.4366167   -.2460042
          42  |   .0232529   .0314064     0.74   0.465    -.0411878    .0876935
          43  |   -.274361   .0367776    -7.46   0.000    -.3498224   -.1988997
          44  |   -.278612    .026223   -10.62   0.000    -.3324172   -.2248069
          45  |  -.1720409   .0143999   -11.95   0.000    -.2015871   -.1424947
          51  |  -.4276558   .0483193    -8.85   0.000    -.5267988   -.3285128
          52  |  -.2958626   .0495625    -5.97   0.000    -.3975563   -.1941688
          53  |  -.2296632   .0441896    -5.20   0.000    -.3203328   -.1389936
          61  |  -.3153697   .0514322    -6.13   0.000    -.4208999   -.2098394
          62  |  -.2985773   .0565748    -5.28   0.000    -.4146592   -.1824954
          63  |  -.4797629   .0694461    -6.91   0.000    -.6222545   -.3372713
          64  |  -.2122747   .0255387    -8.31   0.000    -.2646757   -.1598736
          65  |  -.0919524   .0193013    -4.76   0.000    -.1315553   -.0523495
              |
         cell |
           2  |  -.0581193   .0581246    -1.00   0.326    -.1773812    .0611425
           3  |  -.1660163   .0412279    -4.03   0.000    -.2506089   -.0814237
           4  |  -.1329644   .0568694    -2.34   0.027    -.2496508    -.016278
           5  |  -.1056352   .0417685    -2.53   0.018    -.1913371   -.0199333
           6  |   -.079545   .0446757    -1.78   0.086    -.1712119    .0121219
           7  |  -.1402718   .0477791    -2.94   0.007    -.2383065   -.0422371
           8  |  -.1574798   .0462867    -3.40   0.002    -.2524523   -.0625072
           9  |  -.1643831   .0517105    -3.18   0.004    -.2704842   -.0582819
          10  |  -.1736707    .050814    -3.42   0.002    -.2779325    -.069409
          11  |  -.2217898   .0594349    -3.73   0.001    -.3437402   -.0998393
          12  |  -.1582167   .0503459    -3.14   0.004    -.2615179   -.0549156
          13  |  -.2037752    .057592    -3.54   0.001    -.3219443   -.0856062
          14  |  -.1943551   .0653246    -2.98   0.006    -.3283901   -.0603201
          15  |  -.2030144   .0678182    -2.99   0.006    -.3421658    -.063863
          16  |  -.2349747   .0737462    -3.19   0.004    -.3862895   -.0836599
          17  |   -.310318    .088986    -3.49   0.002    -.4929022   -.1277338
          18  |   -.315899   .0954132    -3.31   0.003    -.5116706   -.1201273
          19  |   .3258572   .2836276     1.15   0.261    -.2560987     .907813
          20  |   .2191109     .26745     0.82   0.420    -.3296511     .767873
          21  |   .2322766   .2766303     0.84   0.408    -.3353219    .7998752
          22  |   .1753132   .2623945     0.67   0.510    -.3630759    .7137023
          23  |   .1694824    .260765     0.65   0.521    -.3655631    .7045279
          24  |   .1630423   .2662463     0.61   0.545      -.38325    .7093345
          25  |   .2027129   .2522517     0.80   0.429    -.3148649    .7202908
          26  |   .1742265   .2533237     0.69   0.497    -.3455508    .6940038
          27  |   .1167403   .2388633     0.49   0.629    -.3733667    .6068473
          28  |   .0875349   .2059526     0.43   0.674     -.335045    .5101147
          29  |   .1287228   .2195213     0.59   0.562    -.3216976    .5791433
          30  |   .1324837   .2209945     0.60   0.554    -.3209595     .585927
          31  |    .183769   .2211293     0.83   0.413    -.2699509    .6374888
          32  |   .1862978   .2266146     0.82   0.418     -.278677    .6512725
          33  |   .2068084   .2261935     0.91   0.369    -.2573022    .6709191
          34  |   .2106539   .2286392     0.92   0.365    -.2584749    .6797827
          35  |   .2587021   .2364227     1.09   0.284    -.2263972    .7438015
          36  |   .2378412   .2275205     1.05   0.305    -.2289922    .7046746
          37  |   .3526224   .2090282     1.69   0.103    -.0762679    .7815128
          38  |   .0203254   .2175651     0.09   0.926    -.4260812    .4667321
          39  |   .1908646   .2382656     0.80   0.430    -.2980161    .6797454
          40  |   .2122547    .220941     0.96   0.345    -.2410787    .6655881
          41  |   .2061669   .2347605     0.88   0.388    -.2755218    .6878556
          42  |   .2026462   .2311606     0.88   0.388    -.2716562    .6769486
          43  |   .1973887   .2217479     0.89   0.381    -.2576003    .6523777
          44  |   .2578037   .2213275     1.16   0.254    -.1963229    .7119303
          45  |   .3121031   .2240262     1.39   0.175    -.1475607    .7717669
          46  |   .2403433   .2057118     1.17   0.253    -.1817424     .662429
          47  |   .2217891   .2002128     1.11   0.278    -.1890135    .6325918
          48  |   .2569436   .1925366     1.33   0.193    -.1381089    .6519961
          49  |   .2499132   .2031855     1.23   0.229     -.166989    .6668154
          50  |   .2468878   .1845699     1.34   0.192    -.1318184    .6255939
          51  |   .1801069   .1775572     1.01   0.319    -.1842104    .5444242
          52  |   .2166183   .1754098     1.23   0.227    -.1432928    .5765295
          53  |   .2312423    .162139     1.43   0.165    -.1014396    .5639241
          54  |   .1339693   .1540925     0.87   0.392    -.1822025     .450141
          55  |   .1675932   .1723375     0.97   0.339    -.1860141    .5212005
          56  |   .2224592   .1841161     1.21   0.237    -.1553158    .6002343
          57  |   .3461949    .348953     0.99   0.330    -.3697975    1.062187
          58  |   .1483183   .2312992     0.64   0.527    -.3262685    .6229052
          59  |   .2208704   .2387621     0.93   0.363     -.269029    .7107697
          60  |   .1464326   .2033165     0.72   0.478    -.2707384    .5636036
          61  |   .1138363   .1923985     0.59   0.559    -.2809329    .5086055
          62  |   .0721662   .2163296     0.33   0.741    -.3717056    .5160379
          63  |   .1404909   .1743723     0.81   0.427    -.2172915    .4982733
          64  |   .0320622   .2106667     0.15   0.880    -.4001902    .4643147
          65  |   .0226265   .2130102     0.11   0.916    -.4144344    .4596874
          66  |   .0858585   .2055033     0.42   0.679    -.3357995    .5075165
          67  |   .0451496   .1697516     0.27   0.792    -.3031519     .393451
          68  |   .2811636   .1787677     1.57   0.127    -.0856374    .6479647
          69  |  -.0329312   .1721804    -0.19   0.850    -.3862161    .3203538
          70  |  -.0196785   .1756111    -0.11   0.912    -.3800028    .3406457
          71  |          0  (omitted)
              |
    prov2Xyob |   .0094475   .0050782     1.86   0.074    -.0009722    .0198672
    prov3Xyob |   .0162492   .0015463    10.51   0.000     .0130765    .0194219
    prov4Xyob |   .0140937   .0040726     3.46   0.002     .0057374      .02245
    prov5Xyob |   .0086765   .0030552     2.84   0.008     .0024077    .0149452
    prov6Xyob |   .0052009   .0006219     8.36   0.000      .003925    .0064769
    prov7Xyob |   .0157868   .0048876     3.23   0.003     .0057582    .0258153
    prov8Xyob |   .0052519   .0033068     1.59   0.124    -.0015331    .0120369
    prov9Xyob |   .0096405    .002834     3.40   0.002     .0038256    .0154553
   prov10Xyob |   .0260698   .0014772    17.65   0.000     .0230388    .0291007
   prov11Xyob |   .0039817   .0022075     1.80   0.082    -.0005477    .0085112
   prov12Xyob |   .0203537   .0047158     4.32   0.000     .0106777    .0300297
   prov13Xyob |   .0195825   .0014815    13.22   0.000     .0165426    .0226223
   prov14Xyob |   .0087042   .0027424     3.17   0.004     .0030773    .0143311
   prov15Xyob |   .0223588   .0037091     6.03   0.000     .0147483    .0299693
   prov16Xyob |    .027661   .0027214    10.16   0.000     .0220771     .033245
   prov17Xyob |  -.0031513   .0015952    -1.98   0.059    -.0064243    .0001217
   prov18Xyob |   .0074615    .002644     2.82   0.009     .0020365    .0128864
   prov19Xyob |   .0125806   .0013206     9.53   0.000      .009871    .0152902
   prov20Xyob |    .008515   .0007792    10.93   0.000     .0069162    .0101139
   prov21Xyob |   .0200284    .003111     6.44   0.000     .0136452    .0264116
   prov22Xyob |   .0127101   .0027881     4.56   0.000     .0069893    .0184308
   prov23Xyob |   .0031569    .002539     1.24   0.224    -.0020527    .0083665
   prov24Xyob |   .0142822   .0033925     4.21   0.000     .0073213    .0212431
   prov25Xyob |   .0147564   .0031324     4.71   0.000     .0083292    .0211835
   prov26Xyob |   .0233286   .0043978     5.30   0.000     .0143051    .0323521
   prov27Xyob |   .0057427   .0010288     5.58   0.000     .0036319    .0078536
   prov28Xyob |   .0118469   .0009503    12.47   0.000     .0098972    .0137967
        _cons |   .4210837   .0758275     5.55   0.000     .2654985    .5766688
-------------------------------------------------------------------------------

. outreg2 using "table1_2.xls", keep(order1Xfine_e order2Xfine_e order3Xfine_e) append dec(3)
table1_2.xls
dir : seeout

. 
. **** Table 3 ****
. use "time_data_reg", clear 

. set more off 

. keep if birth_year <= 2001 
(34387 observations deleted)

. gen m_initial_age = int(m_birth_age - time_2/12)
(3051992 missing values generated)

. replace m_initial_age = m_birth_age - time_y2 if mi(m_initial_age)
(1582838 real changes made)

. replace m_initial_age = 10 if m_initial_age <= 10 
(10103 real changes made)

. replace m_initial_age = 40 if m_initial_age >= 40 & !mi(m_initial_age)
(282 real changes made)

. gen fine_u = fine if order == 1 
(2757843 missing values generated)

. egen fine_use = max(fine_u), by(hhid year)
(7002 missing values generated)

. drop fine_e 

. gen fine_e = fine_use
(7002 missing values generated)

. keep if order == 2 
(4231667 observations deleted)

. replace time_2 = time_2/12 
(1271175 real changes made)

. replace time_2 = time_y2 if mi(time_2)
(570697 real changes made)

. replace time_2 = . if time_2 >= 10 
(19476 real changes made, 19476 to missing)

. gen twinsXpolicy = twins*(birth_year >=1980)

. gl control_2 = "rural i.h_m_edu i.h_fm_han i.m_initial_age i.prov prov*Xyob i.cell"

. 
. /* Table 3 */ 
. reg time_2 twinsXpolicy twins $control_2 [aw = weight],  cluster(cluster_id)
(sum of wgt is   2.0170e+06)

Linear regression                                      Number of obs = 1822396
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.4674
                                                       Root MSE      =  1.1929

                             (Std. Err. adjusted for 28 clusters in cluster_id)
-------------------------------------------------------------------------------
              |               Robust
       time_2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
 twinsXpolicy |   .0778972   .0274049     2.84   0.008     .0216671    .1341273
        twins |   .1890102   .0164227    11.51   0.000     .1553136    .2227069
        rural |  -.2453168   .0196355   -12.49   0.000    -.2856056    -.205028
              |
      h_m_edu |
           2  |  -.0206817   .0185655    -1.11   0.275    -.0587749    .0174114
           3  |   .0249829   .0301844     0.83   0.415    -.0369504    .0869163
           4  |   .4904151   .0347555    14.11   0.000     .4191027    .5617275
              |
   1.h_fm_han |   .0360827   .0559345     0.65   0.524    -.0786854    .1508509
              |
m_initial_age |
          11  |  -.5532998   .0539455   -10.26   0.000    -.6639868   -.4426128
          12  |  -1.016098   .0758821   -13.39   0.000    -1.171796   -.8604011
          13  |  -1.584449   .0901059   -17.58   0.000    -1.769331   -1.399567
          14  |   -2.20296   .1035097   -21.28   0.000    -2.415344   -1.990576
          15  |  -2.808464   .1022451   -27.47   0.000    -3.018254   -2.598675
          16  |  -3.326157   .0950109   -35.01   0.000    -3.521103    -3.13121
          17  |   -3.76634   .0823258   -45.75   0.000    -3.935259   -3.597422
          18  |   -4.11041   .0747712   -54.97   0.000    -4.263828   -3.956992
          19  |  -4.391613   .0683582   -64.24   0.000    -4.531872   -4.251353
          20  |  -4.595094   .0623296   -73.72   0.000    -4.722984   -4.467204
          21  |    -4.7766   .0587361   -81.32   0.000    -4.897117   -4.656084
          22  |  -4.911753    .059225   -82.93   0.000    -5.033272   -4.790233
          23  |  -5.033813    .060485   -83.22   0.000    -5.157918   -4.909708
          24  |   -5.12235   .0614607   -83.34   0.000    -5.248457   -4.996243
          25  |  -5.171205    .061514   -84.07   0.000    -5.297422   -5.044989
          26  |  -5.188964   .0686923   -75.54   0.000    -5.329909   -5.048019
          27  |   -5.15468    .065961   -78.15   0.000    -5.290021   -5.019339
          28  |  -5.150981   .0714972   -72.04   0.000    -5.297681   -5.004281
          29  |  -5.087599   .0690775   -73.65   0.000    -5.229335   -4.945864
          30  |  -4.991064   .0665823   -74.96   0.000     -5.12768   -4.854448
          31  |  -5.031045   .0742528   -67.76   0.000    -5.183399   -4.878691
          32  |  -5.051611   .0752224   -67.16   0.000    -5.205955   -4.897268
          33  |   -5.00127   .0858469   -58.26   0.000    -5.177413   -4.825127
          34  |  -4.981083   .0683084   -72.92   0.000     -5.12124   -4.840925
          35  |  -5.026965   .1186936   -42.35   0.000    -5.270504   -4.783426
          36  |  -4.934852   .1068199   -46.20   0.000    -5.154028   -4.715675
          37  |  -4.955342   .1391744   -35.61   0.000    -5.240904    -4.66978
          38  |  -4.932994   .1525893   -32.33   0.000    -5.246082   -4.619907
          39  |  -4.960829   .2322639   -21.36   0.000    -5.437395   -4.484262
          40  |  -4.891715   .1196266   -40.89   0.000    -5.137169   -4.646262
              |
         prov |
          12  |  -.4450095   .0197453   -22.54   0.000    -.4855234   -.4044956
          13  |  -.6414302   .0224676   -28.55   0.000    -.6875299   -.5953304
          14  |   -.583008   .0498475   -11.70   0.000    -.6852866   -.4807294
          15  |  -1.332756   .0301314   -44.23   0.000    -1.394581   -1.270932
          21  |   -1.25037   .0070455  -177.47   0.000    -1.264827   -1.235914
          22  |  -1.221052   .0264107   -46.23   0.000    -1.275242   -1.166862
          23  |  -1.225569     .02688   -45.59   0.000    -1.280722   -1.170416
          31  |   .1714521   .0068864    24.90   0.000     .1573224    .1855818
          32  |  -.3317349   .0280679   -11.82   0.000    -.3893256   -.2741443
          33  |  -1.512147   .0293246   -51.57   0.000    -1.572316   -1.451978
          34  |  -.6725116   .0318158   -21.14   0.000    -.7377922    -.607231
          35  |  -.9053622   .0360605   -25.11   0.000    -.9793523   -.8313721
          36  |  -.9221722   .0401272   -22.98   0.000    -1.004506    -.839838
          37  |  -.9833084   .0177856   -55.29   0.000    -1.019802   -.9468153
          41  |  -.4838084   .0249472   -19.39   0.000    -.5349957    -.432621
          42  |  -.6678265   .0248797   -26.84   0.000    -.7188754   -.6167776
          43  |  -.9320899   .0263281   -35.40   0.000    -.9861108   -.8780691
          44  |  -.1001786   .0367341    -2.73   0.011    -.1755507   -.0248065
          45  |  -.3377651   .0304415   -11.10   0.000    -.4002259   -.2753042
          51  |  -.3365932   .0193454   -17.40   0.000    -.3762868   -.2968997
          52  |  -.2007062   .0411279    -4.88   0.000    -.2850936   -.1163187
          53  |  -.5047722   .0442011   -11.42   0.000    -.5954653   -.4140791
          61  |  -.4963928   .0364064   -13.63   0.000    -.5710927    -.421693
          62  |   -.727838   .0511884   -14.22   0.000    -.8328679   -.6228081
          63  |  -.7528821   .0474691   -15.86   0.000    -.8502808   -.6554835
          64  |  -.5661574   .0469388   -12.06   0.000    -.6624679    -.469847
          65  |  -.6310493   .0271181   -23.27   0.000    -.6866911   -.5754075
              |
    prov2Xyob |   .0226328   .0010193    22.20   0.000     .0205414    .0247242
    prov3Xyob |   .0195535   .0008618    22.69   0.000     .0177853    .0213217
    prov4Xyob |  -.0111947    .002144    -5.22   0.000    -.0155939   -.0067955
    prov5Xyob |   .0319207     .00091    35.08   0.000     .0300536    .0337877
    prov6Xyob |   .0692266   .0010565    65.52   0.000     .0670588    .0713944
    prov7Xyob |   .0352324   .0009912    35.54   0.000     .0331986    .0372662
    prov8Xyob |   .0237687   .0010456    22.73   0.000     .0216233    .0259141
    prov9Xyob |  -.0189816   .0009186   -20.66   0.000    -.0208663   -.0170968
   prov10Xyob |   -.007257   .0012393    -5.86   0.000    -.0097999   -.0047142
   prov11Xyob |   .0559749   .0005932    94.37   0.000     .0547578     .057192
   prov12Xyob |  -.0072157   .0013377    -5.39   0.000    -.0099605    -.004471
   prov13Xyob |  -.0043543   .0010968    -3.97   0.000    -.0066047   -.0021039
   prov14Xyob |  -.0101975   .0013069    -7.80   0.000     -.012879    -.007516
   prov15Xyob |   .0462142   .0006014    76.84   0.000     .0449802    .0474483
   prov16Xyob |   .0052517   .0010836     4.85   0.000     .0030284     .007475
   prov17Xyob |  -.0017998   .0009349    -1.93   0.065    -.0037182    .0001185
   prov18Xyob |    .007311   .0007532     9.71   0.000     .0057656    .0088564
   prov19Xyob |   -.035285   .0020776   -16.98   0.000    -.0395479   -.0310221
   prov20Xyob |  -.0270563   .0012126   -22.31   0.000    -.0295443   -.0245683
   prov21Xyob |  -.0073235   .0006266   -11.69   0.000     -.008609   -.0060379
   prov22Xyob |  -.0345493   .0022406   -15.42   0.000    -.0391466    -.029952
   prov23Xyob |  -.0189716   .0024761    -7.66   0.000    -.0240521   -.0138911
   prov24Xyob |  -.0078473   .0015939    -4.92   0.000    -.0111176   -.0045769
   prov25Xyob |   -.012349   .0022193    -5.56   0.000    -.0169027   -.0077953
   prov26Xyob |  -.0171883   .0023597    -7.28   0.000      -.02203   -.0123466
   prov27Xyob |  -.0305235   .0024363   -12.53   0.000    -.0355224   -.0255247
   prov28Xyob |  -.0151075   .0018134    -8.33   0.000    -.0188284   -.0113867
              |
         cell |
           3  |   .6026956   .0225449    26.73   0.000     .5564371     .648954
           4  |   .9302677   .0315867    29.45   0.000      .865457    .9950783
           5  |   1.087855   .0418895    25.97   0.000     1.001905    1.173805
           6  |   1.058884   .0470608    22.50   0.000      .962323    1.155445
           7  |   1.048594   .0474435    22.10   0.000      .951248     1.14594
           8  |   1.107927    .056863    19.48   0.000     .9912537      1.2246
           9  |   1.182172   .0575128    20.55   0.000     1.064166    1.300179
          10  |   1.253287    .059537    21.05   0.000     1.131127    1.375447
          11  |   1.261618   .0627818    20.10   0.000       1.1328    1.390436
          12  |   1.324678   .0645893    20.51   0.000     1.192151    1.457204
          13  |   1.407044   .0682221    20.62   0.000     1.267064    1.547025
          14  |   1.493919   .0724185    20.63   0.000     1.345329     1.64251
          15  |   1.558887   .0753757    20.68   0.000     1.404229    1.713545
          16  |   1.608431   .0850244    18.92   0.000     1.433976    1.782887
          17  |   1.557578   .0818085    19.04   0.000      1.38972    1.725435
          18  |   1.628372   .0856076    19.02   0.000      1.45272    1.804024
          19  |  -.6686671   .1191416    -5.61   0.000    -.9131255   -.4242087
          20  |   .0318473   .0536774     0.59   0.558    -.0782896    .1419841
          21  |   .4590475   .0592606     7.75   0.000     .3374548    .5806403
          22  |   .7588482   .0644294    11.78   0.000       .62665    .8910464
          23  |   1.002811   .0670102    14.97   0.000     .8653173    1.140305
          24  |   1.179104   .0713654    16.52   0.000     1.032675    1.325534
          25  |    1.34638    .075241    17.89   0.000     1.191999    1.500762
          26  |   1.428469   .0850531    16.80   0.000     1.253954    1.602983
          27  |   1.474357   .0809031    18.22   0.000     1.308357    1.640356
          28  |    1.43635    .086521    16.60   0.000     1.258824    1.613877
          29  |   1.428222   .0845674    16.89   0.000     1.254704     1.60174
          30  |   1.355471   .0866334    15.65   0.000     1.177714    1.533228
          31  |   1.372378   .0883468    15.53   0.000     1.191105    1.553651
          32  |   1.475861   .0948659    15.56   0.000     1.281213     1.67051
          33  |   1.684813   .1037513    16.24   0.000     1.471933    1.897693
          34  |   1.718353   .0845486    20.32   0.000     1.544873    1.891832
          35  |   1.632882   .0769153    21.23   0.000     1.475065    1.790699
          36  |   1.646917   .0845167    19.49   0.000     1.473502    1.820331
          37  |   1.726256   .0847733    20.36   0.000     1.552316    1.900197
          38  |   -1.15208   .0606715   -18.99   0.000    -1.276568   -1.027593
          39  |   -.044203   .0926825    -0.48   0.637    -.2343717    .1459656
          40  |   .3480818   .1092558     3.19   0.004     .1239073    .5722563
          41  |   .6413613   .1095321     5.86   0.000     .4166199    .8661027
          42  |   .8319717   .1100823     7.56   0.000     .6061015    1.057842
          43  |   .9633396   .1108372     8.69   0.000     .7359205    1.190759
          44  |   1.085393   .1095615     9.91   0.000     .8605911    1.310194
          45  |   1.191064   .1127812    10.56   0.000     .9596559    1.422472
          46  |   1.278447   .1072094    11.92   0.000     1.058472    1.498423
          47  |   1.437052   .0939246    15.30   0.000     1.244334    1.629769
          48  |   1.637483   .0797702    20.53   0.000     1.473808    1.801158
          49  |   1.805848   .0692585    26.07   0.000     1.663741    1.947954
          50  |   2.033011   .0599688    33.90   0.000     1.909965    2.156057
          51  |    2.28207   .0604388    37.76   0.000      2.15806     2.40608
          52  |   2.499939   .0656301    38.09   0.000     2.365277    2.634601
          53  |   2.709933   .0749472    36.16   0.000     2.556154    2.863712
          54  |    2.89369   .0861213    33.60   0.000     2.716984    3.070396
          55  |    3.14597   .0956891    32.88   0.000     2.949632    3.342308
          56  |   3.305712   .0981706    33.67   0.000     3.104283    3.507142
          58  |  -.0331477   .1472239    -0.23   0.824    -.3352261    .2689307
          59  |    .372566   .1417153     2.63   0.014     .0817902    .6633418
          60  |   .6875928   .1348971     5.10   0.000     .4108067    .9643788
          61  |   .9270193   .1259809     7.36   0.000     .6685279    1.185511
          62  |   1.192926   .1125932    10.60   0.000     .9619039    1.423948
          63  |   1.440317   .0949229    15.17   0.000     1.245552    1.635083
          64  |   1.712097   .0883709    19.37   0.000     1.530775    1.893419
          65  |   1.986201    .074718    26.58   0.000     1.832892     2.13951
          66  |   2.242335   .0692632    32.37   0.000     2.100219    2.384451
          67  |   2.477482   .0734454    33.73   0.000     2.326784    2.628179
          68  |   2.626733   .0775889    33.85   0.000     2.467533    2.785932
          69  |   2.847888   .0808511    35.22   0.000     2.681995    3.013781
          70  |   2.990642   .0784569    38.12   0.000     2.829661    3.151622
          71  |   3.154516   .0922453    34.20   0.000     2.965244    3.343787
              |
        _cons |   6.497005   .0996061    65.23   0.000     6.292631     6.70138
-------------------------------------------------------------------------------

. outreg2 using "table3.xls", keep(twinsXpolicy twins) replace dec(3)
table3.xls
dir : seeout

. 
. reg time_2 twinsXpolicy twins $control_2 [aw = weight] if h_fm_han == 1, cluster(cluster_id)
(sum of wgt is   1.8670e+06)

Linear regression                                      Number of obs = 1690608
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.4711
                                                       Root MSE      =  1.1895

                             (Std. Err. adjusted for 28 clusters in cluster_id)
-------------------------------------------------------------------------------
              |               Robust
       time_2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
 twinsXpolicy |   .0765275   .0282905     2.71   0.012     .0184801    .1345749
        twins |   .1826161   .0166955    10.94   0.000     .1483597    .2168725
        rural |  -.2453516   .0202525   -12.11   0.000    -.2869064   -.2037969
              |
      h_m_edu |
           2  |  -.0238355   .0188987    -1.26   0.218    -.0626125    .0149415
           3  |    .018958   .0295642     0.64   0.527    -.0417028    .0796188
           4  |   .4803252   .0330948    14.51   0.000     .4124202    .5482302
              |
   1.h_fm_han |   .1733442   .0034058    50.90   0.000      .166356    .1803324
              |
m_initial_age |
          11  |  -.5205531   .0420037   -12.39   0.000    -.6067376   -.4343686
          12  |    -.96391    .068089   -14.16   0.000    -1.103617   -.8242029
          13  |  -1.518784   .0812595   -18.69   0.000    -1.685515   -1.352053
          14  |  -2.150054   .1023161   -21.01   0.000     -2.35999   -1.940119
          15  |  -2.775407   .1055986   -26.28   0.000    -2.992077   -2.558736
          16  |  -3.311967   .0994685   -33.30   0.000     -3.51606   -3.107875
          17  |  -3.762513   .0877557   -42.87   0.000    -3.942573   -3.582453
          18  |  -4.113295   .0801488   -51.32   0.000    -4.277747   -3.948843
          19  |  -4.397823   .0738928   -59.52   0.000    -4.549438   -4.246207
          20  |  -4.604366   .0675427   -68.17   0.000    -4.742952   -4.465779
          21  |  -4.787948   .0637323   -75.13   0.000    -4.918716    -4.65718
          22  |  -4.925969   .0642273   -76.70   0.000    -5.057752   -4.794185
          23  |  -5.051203      .0657   -76.88   0.000    -5.186008   -4.916398
          24  |   -5.13902   .0666835   -77.07   0.000    -5.275844   -5.002197
          25  |  -5.194689   .0665941   -78.01   0.000    -5.331328   -5.058049
          26  |  -5.213109   .0739718   -70.47   0.000    -5.364887   -5.061331
          27  |  -5.181835   .0699629   -74.07   0.000    -5.325387   -5.038283
          28  |  -5.192594    .073524   -70.62   0.000    -5.343453   -5.041736
          29  |  -5.123749   .0708112   -72.36   0.000    -5.269041   -4.978456
          30  |  -5.020286   .0713717   -70.34   0.000    -5.166728   -4.873843
          31  |  -5.063893   .0754804   -67.09   0.000    -5.218766    -4.90902
          32  |  -5.091103   .0789921   -64.45   0.000    -5.253181   -4.929025
          33  |  -5.061263    .078885   -64.16   0.000    -5.223121   -4.899404
          34  |  -5.019733   .0722444   -69.48   0.000    -5.167966   -4.871499
          35  |  -5.096686    .106135   -48.02   0.000    -5.314457   -4.878915
          36  |  -5.027364   .0950174   -52.91   0.000    -5.222323   -4.832404
          37  |  -5.000974   .1497314   -33.40   0.000    -5.308197    -4.69375
          38  |  -4.984666   .1611794   -30.93   0.000    -5.315379   -4.653954
          39  |  -5.016111   .2379992   -21.08   0.000    -5.504445   -4.527777
          40  |  -4.982081   .1214618   -41.02   0.000      -5.2313   -4.732862
              |
         prov |
          12  |  -.4389295   .0205906   -21.32   0.000     -.481178    -.396681
          13  |  -.6207517    .023007   -26.98   0.000    -.6679582   -.5735453
          14  |  -.6013738   .0499814   -12.03   0.000    -.7039272   -.4988205
          15  |  -1.357931   .0299136   -45.40   0.000    -1.419309   -1.296554
          21  |  -1.220919   .0073856  -165.31   0.000    -1.236073   -1.205765
          22  |  -1.224813   .0267509   -45.79   0.000    -1.279701   -1.169924
          23  |   -1.22853   .0265446   -46.28   0.000    -1.282995   -1.174065
          31  |    .173428   .0069447    24.97   0.000     .1591787    .1876772
          32  |  -.3373786   .0280507   -12.03   0.000    -.3949339   -.2798233
          33  |  -1.522398   .0293441   -51.88   0.000    -1.582607   -1.462188
          34  |  -.6836356   .0325117   -21.03   0.000    -.7503441   -.6169272
          35  |  -.9166914   .0362048   -25.32   0.000    -.9909775   -.8424054
          36  |  -.9350239    .040669   -22.99   0.000     -1.01847   -.8515779
          37  |   -.980541   .0182957   -53.59   0.000    -1.018081   -.9430013
          41  |   -.485482   .0259539   -18.71   0.000    -.5387351   -.4322289
          42  |  -.6514082   .0259394   -25.11   0.000    -.7046314    -.598185
          43  |  -.9195923   .0272067   -33.80   0.000    -.9754158   -.8637688
          44  |  -.1064246   .0366708    -2.90   0.007    -.1816667   -.0311824
          45  |  -.3161402   .0263465   -12.00   0.000    -.3701988   -.2620817
          51  |  -.3812619   .0195996   -19.45   0.000    -.4214769   -.3410469
          52  |  -.2452344   .0388513    -6.31   0.000    -.3249506   -.1655181
          53  |  -.4974181   .0431271   -11.53   0.000    -.5859076   -.4089286
          61  |  -.5095542    .036835   -13.83   0.000    -.5851335   -.4339749
          62  |  -.7598541   .0514284   -14.77   0.000    -.8653764   -.6543317
          63  |  -.9068689   .0458681   -19.77   0.000    -1.000983   -.8127552
          64  |  -.6736489   .0441234   -15.27   0.000    -.7641827   -.5831152
          65  |  -.6672878   .0100937   -66.11   0.000    -.6879983   -.6465772
              |
    prov2Xyob |   .0224252   .0010751    20.86   0.000     .0202192    .0246311
    prov3Xyob |   .0180322   .0009003    20.03   0.000     .0161849    .0198796
    prov4Xyob |  -.0105526   .0021844    -4.83   0.000    -.0150346   -.0060706
    prov5Xyob |   .0342323   .0007173    47.72   0.000     .0327604    .0357042
    prov6Xyob |   .0663005   .0008518    77.83   0.000     .0645526    .0680483
    prov7Xyob |   .0325052   .0010006    32.49   0.000     .0304522    .0345581
    prov8Xyob |    .023029   .0010107    22.79   0.000     .0209552    .0251028
    prov9Xyob |  -.0190846   .0009221   -20.70   0.000    -.0209767   -.0171926
   prov10Xyob |  -.0070399   .0012125    -5.81   0.000    -.0095277   -.0045522
   prov11Xyob |   .0560788   .0006529    85.89   0.000     .0547392    .0574185
   prov12Xyob |   -.006793    .001394    -4.87   0.000    -.0096532   -.0039327
   prov13Xyob |  -.0040375   .0011223    -3.60   0.001    -.0063404   -.0017347
   prov14Xyob |  -.0099477   .0013619    -7.30   0.000    -.0127421   -.0071534
   prov15Xyob |   .0459752   .0006413    71.69   0.000     .0446593    .0472912
   prov16Xyob |   .0053016   .0011556     4.59   0.000     .0029305    .0076727
   prov17Xyob |  -.0032057   .0010114    -3.17   0.004    -.0052809   -.0011305
   prov18Xyob |   .0056064     .00071     7.90   0.000     .0041496    .0070632
   prov19Xyob |  -.0345905   .0020768   -16.66   0.000    -.0388516   -.0303293
   prov20Xyob |  -.0300946   .0013404   -22.45   0.000    -.0328449   -.0273443
   prov21Xyob |  -.0047044   .0005573    -8.44   0.000    -.0058479    -.003561
   prov22Xyob |  -.0352901   .0020809   -16.96   0.000    -.0395598   -.0310205
   prov23Xyob |  -.0173124   .0024365    -7.11   0.000    -.0223118   -.0123131
   prov24Xyob |  -.0073976   .0016351    -4.52   0.000    -.0107526   -.0040426
   prov25Xyob |  -.0107368   .0022522    -4.77   0.000    -.0153579   -.0061157
   prov26Xyob |  -.0064539   .0021833    -2.96   0.006    -.0109336   -.0019742
   prov27Xyob |  -.0236054   .0021992   -10.73   0.000    -.0281177   -.0190931
   prov28Xyob |   .0000991   .0008103     0.12   0.904    -.0015635    .0017616
              |
         cell |
           3  |   .6003284   .0242597    24.75   0.000     .5505517    .6501051
           4  |     .92485   .0328411    28.16   0.000     .8574657    .9922343
           5  |   1.078825   .0425548    25.35   0.000     .9915096     1.16614
           6  |    1.04797   .0477731    21.94   0.000     .9499478    1.145992
           7  |   1.040907   .0481265    21.63   0.000     .9421596    1.139654
           8  |   1.096528   .0570157    19.23   0.000     .9795415    1.213515
           9  |   1.171635    .058523    20.02   0.000     1.051555    1.291714
          10  |   1.245484   .0608526    20.47   0.000     1.120625    1.370343
          11  |   1.256364   .0646775    19.43   0.000     1.123657    1.389072
          12  |   1.321022   .0667875    19.78   0.000     1.183986    1.458059
          13  |   1.404266   .0700183    20.06   0.000       1.2606    1.547932
          14  |   1.493868   .0739699    20.20   0.000     1.342094    1.645642
          15  |   1.560003   .0758094    20.58   0.000     1.404455    1.715551
          16  |   1.610635   .0855269    18.83   0.000     1.435149    1.786122
          17  |   1.558171   .0820722    18.99   0.000     1.389773    1.726569
          18  |   1.629569   .0862856    18.89   0.000     1.452526    1.806613
          19  |  -.6751665   .1230882    -5.49   0.000    -.9277225   -.4226104
          20  |   .0327547   .0561557     0.58   0.565    -.0824673    .1479767
          21  |    .456482   .0605235     7.54   0.000     .3322981    .5806658
          22  |   .7519329   .0655263    11.48   0.000      .617484    .8863819
          23  |   .9985588   .0685448    14.57   0.000     .8579165    1.139201
          24  |   1.176553     .07279    16.16   0.000       1.0272    1.325906
          25  |   1.345803   .0759348    17.72   0.000     1.189997    1.501608
          26  |   1.428384   .0853664    16.73   0.000     1.253227    1.603541
          27  |   1.476183   .0805704    18.32   0.000     1.310867      1.6415
          28  |   1.435422   .0864196    16.61   0.000     1.258104     1.61274
          29  |   1.428988   .0852476    16.76   0.000     1.254074    1.603902
          30  |   1.351688   .0888768    15.21   0.000     1.169328    1.534048
          31  |   1.369406   .0925937    14.79   0.000      1.17942    1.559393
          32  |    1.47742   .0983932    15.02   0.000     1.275534    1.679306
          33  |   1.695409   .1062663    15.95   0.000     1.477369     1.91345
          34  |   1.725249   .0855862    20.16   0.000      1.54964    1.900857
          35  |   1.634796    .079126    20.66   0.000     1.472442    1.797149
          36  |   1.643775   .0864004    19.03   0.000     1.466496    1.821054
          37  |   1.720827   .0869369    19.79   0.000     1.542447    1.899207
          38  |  -1.138841   .0611584   -18.62   0.000    -1.264327   -1.013354
          39  |  -.0634217    .091765    -0.69   0.495     -.251708    .1248646
          40  |   .3367166   .1125781     2.99   0.006     .1057253    .5677079
          41  |   .6289011   .1117128     5.63   0.000     .3996853    .8581168
          42  |    .821411   .1124979     7.30   0.000     .5905843    1.052238
          43  |   .9523354    .113745     8.37   0.000     .7189498    1.185721
          44  |   1.069622   .1124222     9.51   0.000     .8389507    1.300294
          45  |   1.172969   .1152488    10.18   0.000     .9364975    1.409439
          46  |   1.258127   .1090745    11.53   0.000     1.034324    1.481929
          47  |   1.413839   .0945809    14.95   0.000     1.219775    1.607903
          48  |   1.614821   .0802384    20.13   0.000     1.450185    1.779457
          49  |   1.782792   .0697174    25.57   0.000     1.639744    1.925841
          50  |   2.011332   .0594901    33.81   0.000     1.889269    2.133396
          51  |    2.26627   .0604414    37.50   0.000     2.142255    2.390286
          52  |   2.495625   .0670328    37.23   0.000     2.358085    2.633165
          53  |   2.723035   .0765694    35.56   0.000     2.565927    2.880142
          54  |   2.912515   .0853905    34.11   0.000     2.737308    3.087722
          55  |   3.163436   .0956296    33.08   0.000     2.967221    3.359652
          56  |   3.323948   .0998622    33.29   0.000     3.119048    3.528849
          58  |   -.034171   .1448173    -0.24   0.815    -.3313115    .2629695
          59  |    .362359   .1467466     2.47   0.020     .0612599    .6634582
          60  |   .6706486   .1394677     4.81   0.000     .3844846    .9568127
          61  |   .9029287   .1302335     6.93   0.000     .6357118    1.170146
          62  |   1.162147   .1159926    10.02   0.000     .9241494    1.400144
          63  |   1.405042   .0950705    14.78   0.000     1.209974    1.600111
          64  |   1.675477    .089154    18.79   0.000     1.492548    1.858406
          65  |   1.953225   .0679531    28.74   0.000     1.813797    2.092654
          66  |   2.218998    .066719    33.26   0.000     2.082102    2.355894
          67  |   2.437418   .0714777    34.10   0.000     2.290758    2.584078
          68  |   2.604348   .0781271    33.33   0.000     2.444044    2.764652
          69  |   2.824882   .0837019    33.75   0.000      2.65314    2.996624
          70  |    2.98225     .07793    38.27   0.000      2.82235    3.142149
          71  |   3.160036   .0947756    33.34   0.000     2.965572    3.354499
              |
        _cons |   6.377547   .0726282    87.81   0.000     6.228526    6.526568
-------------------------------------------------------------------------------

. outreg2 using "table3.xls", keep(twinsXpolicy twins) append  dec(3)
table3.xls
dir : seeout

. 
. reg time_2 twinsXpolicy twins $control_2 [aw = weight] if h_fm_han == 0, cluster(cluster_id)
(sum of wgt is   1.5004e+05)

Linear regression                                      Number of obs =  131788
                                                       F( 27,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.4599
                                                       Root MSE      =  1.1913

                             (Std. Err. adjusted for 28 clusters in cluster_id)
-------------------------------------------------------------------------------
              |               Robust
       time_2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
 twinsXpolicy |   .1003763   .1087357     0.92   0.364    -.1227308    .3234835
        twins |    .287718   .0956232     3.01   0.006     .0915155    .4839205
        rural |  -.2597554   .0440292    -5.90   0.000    -.3500959   -.1694149
              |
      h_m_edu |
           2  |  -.0156786   .0534988    -0.29   0.772    -.1254491    .0940918
           3  |   .0612962   .0940815     0.65   0.520     -.131743    .2543355
           4  |   .5658289   .1023015     5.53   0.000     .3559235    .7757343
              |
   0.h_fm_han |  -.2927083   .0162401   -18.02   0.000    -.3260302   -.2593865
              |
m_initial_age |
          11  |  -.8306596   .1369602    -6.06   0.000    -1.111679   -.5496405
          12  |  -1.485927   .1633186    -9.10   0.000    -1.821029   -1.150825
          13  |  -2.190955   .1758934   -12.46   0.000    -2.551859   -1.830052
          14  |  -2.730557   .1848919   -14.77   0.000    -3.109923    -2.35119
          15  |  -3.189687    .165962   -19.22   0.000    -3.530213   -2.849161
          16  |  -3.551078   .1484483   -23.92   0.000    -3.855668   -3.246487
          17  |  -3.893274   .1328098   -29.31   0.000    -4.165777   -3.620771
          18  |  -4.174278   .1139719   -36.63   0.000    -4.408129   -3.940427
          19  |  -4.410093   .1075083   -41.02   0.000    -4.630682   -4.189504
          20  |  -4.572887   .0980883   -46.62   0.000    -4.774148   -4.371627
          21  |  -4.722348   .0914784   -51.62   0.000    -4.910046    -4.53465
          22  |  -4.814014   .0861017   -55.91   0.000     -4.99068   -4.637348
          23  |  -4.888148   .0870154   -56.18   0.000    -5.066689   -4.709608
          24  |  -4.993125   .0808532   -61.76   0.000    -5.159022   -4.827228
          25  |  -4.946825   .0804819   -61.47   0.000     -5.11196    -4.78169
          26  |  -4.981189   .0715259   -69.64   0.000    -5.127948    -4.83443
          27  |  -4.945568   .0808098   -61.20   0.000    -5.111376    -4.77976
          28  |  -4.803617   .0889849   -53.98   0.000    -4.986199   -4.621035
          29  |  -4.804764   .0880635   -54.56   0.000    -4.985455   -4.624073
          30  |  -4.768093    .114091   -41.79   0.000    -5.002188   -4.533997
          31  |  -4.770156   .0929622   -51.31   0.000    -4.960899   -4.579414
          32  |  -4.709512   .1272622   -37.01   0.000    -4.970633   -4.448392
          33  |  -4.602003   .1909701   -24.10   0.000    -4.993842   -4.210165
          34  |  -4.781127   .1676857   -28.51   0.000     -5.12519   -4.437064
          35  |  -4.515107    .249309   -18.11   0.000    -5.026647   -4.003567
          36  |  -4.259412   .5592433    -7.62   0.000    -5.406885    -3.11194
          37  |  -4.449313   .1385848   -32.11   0.000    -4.733666   -4.164961
          38  |  -4.407408   .4019687   -10.96   0.000    -5.232179   -3.582636
          39  |  -4.038048   .5980768    -6.75   0.000      -5.2652   -2.810896
          40  |   -4.01944   .2193405   -18.33   0.000     -4.46949   -3.569391
              |
         prov |
          12  |  -.8016271    .041958   -19.11   0.000    -.8877178   -.7155364
          13  |  -1.536847   .0461494   -33.30   0.000    -1.631537   -1.442156
          14  |   -.941329   .0291956   -32.24   0.000    -1.001233   -.8814246
          15  |   -1.42336   .0342449   -41.56   0.000    -1.493625   -1.353096
          21  |  -1.544606   .0306076   -50.46   0.000    -1.607408   -1.481805
          22  |  -1.357844   .0409054   -33.19   0.000    -1.441775   -1.273913
          23  |   -1.38603    .052029   -26.64   0.000    -1.492784   -1.279275
          31  |   .4351071    .051634     8.43   0.000      .329163    .5410513
          32  |  -.3064356   .0250305   -12.24   0.000    -.3577939   -.2550772
          33  |  -1.342596   .0827254   -16.23   0.000    -1.512334   -1.172857
          34  |   -.731806   .0555821   -13.17   0.000    -.8458511    -.617761
          35  |  -1.022987    .064962   -15.75   0.000    -1.156278   -.8896963
          36  |  -.9022929    .051108   -17.65   0.000    -1.007158   -.7974279
          37  |  -1.344595   .0555003   -24.23   0.000    -1.458472   -1.230717
          41  |  -.7861796   .0628057   -12.52   0.000    -.9150463   -.6573129
          42  |  -1.250182   .0514125   -24.32   0.000    -1.355672   -1.144692
          43  |  -1.131693   .0459713   -24.62   0.000    -1.226018   -1.037368
          44  |  -.5012674    .059358    -8.44   0.000    -.6230601   -.3794748
          45  |  -.5469761   .0545092   -10.03   0.000    -.6588198   -.4351323
          51  |   .1473639   .0602574     2.45   0.021     .0237258    .2710019
          52  |  -.1905241    .059756    -3.19   0.004    -.3131333   -.0679149
          53  |  -.6140916   .0637665    -9.63   0.000    -.7449297   -.4832536
          61  |   -.295008   .0272783   -10.81   0.000    -.3509785   -.2390374
          62  |  -.5287173   .0851542    -6.21   0.000    -.7034392   -.3539953
          63  |  -.5241728   .0820217    -6.39   0.000    -.6924674   -.3558781
          64  |  -.3836166     .07694    -4.99   0.000    -.5414843   -.2257488
          65  |  -.7771619   .0511731   -15.19   0.000    -.8821604   -.6721634
              |
    prov2Xyob |    .038691   .0017972    21.53   0.000     .0350034    .0423786
    prov3Xyob |   .0718837   .0019573    36.73   0.000     .0678677    .0758997
    prov4Xyob |    .022918   .0012665    18.10   0.000     .0203193    .0255167
    prov5Xyob |   .0285065   .0011208    25.43   0.000     .0262068    .0308062
    prov6Xyob |   .0891701   .0018335    48.63   0.000      .085408    .0929321
    prov7Xyob |   .0700867   .0027214    25.75   0.000     .0645028    .0756706
    prov8Xyob |   .0406503   .0028636    14.20   0.000     .0347746     .046526
    prov9Xyob |  -.0384253    .002569   -14.96   0.000    -.0436964   -.0331542
   prov10Xyob |  -.0257618   .0013999   -18.40   0.000    -.0286342   -.0228894
   prov11Xyob |   .0317136   .0020508    15.46   0.000     .0275057    .0359215
   prov12Xyob |  -.0054475    .001803    -3.02   0.005    -.0091469   -.0017481
   prov13Xyob |  -.0016088    .001399    -1.15   0.260    -.0044792    .0012616
   prov14Xyob |  -.0048427   .0022833    -2.12   0.043    -.0095276   -.0001577
   prov15Xyob |   .0531693   .0020599    25.81   0.000     .0489427    .0573959
   prov16Xyob |   .0132946   .0025341     5.25   0.000     .0080951    .0184941
   prov17Xyob |   .0371499   .0016019    23.19   0.000     .0338631    .0404367
   prov18Xyob |   .0244908   .0012603    19.43   0.000      .021905    .0270766
   prov19Xyob |  -.0267432   .0019506   -13.71   0.000    -.0307455   -.0227409
   prov20Xyob |  -.0159746   .0015117   -10.57   0.000    -.0190763   -.0128729
   prov21Xyob |  -.0341942   .0017421   -19.63   0.000    -.0377686   -.0306197
   prov22Xyob |  -.0299304   .0015735   -19.02   0.000    -.0331589   -.0267019
   prov23Xyob |  -.0182908   .0019294    -9.48   0.000    -.0222496   -.0143319
   prov24Xyob |  -.0054623   .0016262    -3.36   0.002    -.0087991   -.0021255
   prov25Xyob |  -.0251926   .0019347   -13.02   0.000    -.0291622   -.0212229
   prov26Xyob |  -.0316748   .0019782   -16.01   0.000    -.0357337   -.0276158
   prov27Xyob |   -.040468    .002029   -19.94   0.000    -.0446313   -.0363048
   prov28Xyob |  -.0155773   .0017344    -8.98   0.000    -.0191359   -.0120186
              |
         cell |
           3  |   .6583106   .0470651    13.99   0.000     .5617411    .7548801
           4  |   .9958055   .0437119    22.78   0.000     .9061161    1.085495
           5  |   1.220535   .0632753    19.29   0.000     1.090705    1.350365
           6  |   1.226005   .0644905    19.01   0.000     1.093682    1.358329
           7  |   1.161271   .0756075    15.36   0.000     1.006137    1.316405
           8  |   1.282659   .0903371    14.20   0.000     1.097303    1.468016
           9  |   1.323997   .0784052    16.89   0.000     1.163123    1.484871
          10  |   1.326088   .0731463    18.13   0.000     1.176004    1.476172
          11  |   1.278205    .085735    14.91   0.000     1.102291    1.454119
          12  |    1.31414   .0816187    16.10   0.000     1.146672    1.481607
          13  |   1.386921   .0903654    15.35   0.000     1.201506    1.572335
          14  |   1.414487   .0817646    17.30   0.000      1.24672    1.582254
          15  |   1.454146   .0950387    15.30   0.000     1.259143     1.64915
          16  |   1.494603   .1040955    14.36   0.000     1.281016    1.708189
          17  |   1.472714    .107585    13.69   0.000     1.251968     1.69346
          18  |   1.526494   .1152152    13.25   0.000     1.290092    1.762896
          20  |   .0542581   .0645461     0.84   0.408    -.0781796    .1866957
          21  |   .4897549   .0674057     7.27   0.000     .3514497    .6280601
          22  |   .8171593   .0730641    11.18   0.000      .667244    .9670745
          23  |   1.002489   .0745305    13.45   0.000      .849565    1.155413
          24  |    1.15233   .0766162    15.04   0.000      .995127    1.309534
          25  |   1.284911   .0893193    14.39   0.000     1.101643    1.468179
          26  |   1.343926   .1033434    13.00   0.000     1.131883    1.555969
          27  |   1.371165   .1179235    11.63   0.000     1.129205    1.613124
          28  |   1.352081   .1211415    11.16   0.000     1.103519    1.600642
          29  |    1.32567   .1101216    12.04   0.000     1.099719    1.551621
          30  |   1.307471   .0889617    14.70   0.000     1.124937    1.490005
          31  |    1.31755   .0921035    14.31   0.000     1.128569    1.506531
          32  |   1.356314   .0965913    14.04   0.000     1.158125    1.554503
          33  |   1.425405   .1059647    13.45   0.000     1.207984    1.642827
          34  |   1.476206   .1177535    12.54   0.000     1.234596    1.717816
          35  |   1.463778   .1042439    14.04   0.000     1.249887    1.677669
          36  |   1.527262   .0993364    15.37   0.000     1.323441    1.731084
          37  |   1.627279   .1157781    14.06   0.000     1.389722    1.864836
          39  |     .05814   .1023547     0.57   0.575    -.1518744    .2681545
          40  |   .3964088   .0861651     4.60   0.000     .2196125     .573205
          41  |   .7131241   .1070421     6.66   0.000     .4934919    .9327563
          42  |   .8688383    .116638     7.45   0.000     .6295169     1.10816
          43  |   1.007031    .115506     8.72   0.000     .7700322     1.24403
          44  |   1.177575   .0960541    12.26   0.000     .9804886    1.374662
          45  |   1.306202   .1083089    12.06   0.000      1.08397    1.528434
          46  |   1.404125   .1185244    11.85   0.000     1.160934    1.647317
          47  |    1.57459   .1129218    13.94   0.000     1.342894    1.806286
          48  |   1.744718   .0949309    18.38   0.000     1.549936      1.9395
          49  |   1.902673   .0790052    24.08   0.000     1.740567    2.064778
          50  |   2.092262   .0862053    24.27   0.000     1.915383     2.26914
          51  |   2.300218    .085178    27.00   0.000     2.125447    2.474989
          52  |   2.423897   .0941182    25.75   0.000     2.230782    2.617011
          53  |   2.516996   .0910028    27.66   0.000     2.330273    2.703718
          54  |    2.64154   .0979549    26.97   0.000     2.440553    2.842527
          55  |   2.887892   .1018281    28.36   0.000     2.678958    3.096826
          56  |   3.081408   .1062753    28.99   0.000     2.863349    3.299467
          58  |   .2788992   .0514836     5.42   0.000     .1732636    .3845349
          59  |   .4385581   .1029417     4.26   0.000     .2273391     .649777
          60  |   .8303624   .1185711     7.00   0.000     .5870746     1.07365
          61  |   1.118321   .1222941     9.14   0.000     .8673947    1.369248
          62  |   1.421816   .0999756    14.22   0.000     1.216683    1.626949
          63  |    1.68962    .108069    15.63   0.000      1.46788    1.911359
          64  |   1.925471   .0971433    19.82   0.000     1.726149    2.124793
          65  |   2.183686   .1309304    16.68   0.000     1.915039    2.452333
          66  |   2.338613   .1093648    21.38   0.000     2.114215    2.563011
          67  |   2.670631   .1122633    23.79   0.000     2.440286    2.900976
          68  |   2.655556   .1137196    23.35   0.000     2.422222    2.888889
          69  |   2.864289   .1263472    22.67   0.000     2.605046    3.123532
          70  |   2.916631   .1339888    21.77   0.000     2.641708    3.191553
          71  |   2.980073   .1126975    26.44   0.000     2.748837    3.211309
              |
        _cons |   6.848497   .1543079    44.38   0.000     6.531883     7.16511
-------------------------------------------------------------------------------

. outreg2 using "table3.xls", keep(twinsXpolicy twins) append  dec(3)
table3.xls
dir : seeout

. 
. 
. ****** CHNS Analysis ****
. use "m10pexam",clear

. keep  height hhid line wave commid t1-t5 gender age 

. 
. drop if height <50 // drop the outliers with shorter than 50 cm 
(5 observations deleted)

. drop if mi(height)
(6093 observations deleted)

. 
. gen age2 = age^2/100
(249 missing values generated)

. gen urban = t2 == 1 

. 
. drop if age > 18 // keep those aged below 18 
(68234 observations deleted)

. * Define Twins * 
. sort hhid wave age

. keep if ((abs(age - age[_n-1]) <= 0.02) & wave == wave[_n-1] & hhid == hhid[_n-1] & line != line[_n-1]) ///
>  | ((abs(age - age[_n+1]) <= 0.02) & wave == wave[_n+1] & hhid == hhid[_n+1] & line != line[_n+1])
(20305 observations deleted)

. gen birth_year = int(wave - age) + 1 

. 
. gen height_mi = mi(height)

. egen height_mi_g = max(height_mi), by(hhid wave)

. drop if height_mi_g == 1
(0 observations deleted)

. drop height_mi height_mi_g

. egen count_twins = sum(1), by(hhid wave) 

. drop if count_twins == 1 
(0 observations deleted)

. drop count_twins 

. 
. duplicates drop 

Duplicates in terms of all variables

(0 observations are duplicates)

. * Calculate the height differences * 
. 
. egen height_max = max(height), by(hhid wave)

. egen height_min = min(height), by(hhid wave)

. 
. gen height_male_i = height * (gender == 1)

. gen height_female_i = height * (gender == 2)

. egen height_male = max(height_male_i), by(hhid wave)

. egen height_female = max(height_female_i), by(hhid wave)

. 
. * Calculate the type of the twins * 
. egen gender_max = max(gender), by(hhid wave)

. egen gender_min = min(gender), by(hhid wave)

. gen type = gender_max if gender_max == gender_min 
(49 missing values generated)

. replace type = 3 if gender_max != gender_min 
(49 real changes made)

. 
. gen height_gap = height_max - height_min 

. 
. gen taller_boy =  height_male > height_female & type == 3

. gen height_mean = (height_max +height_min)/2

. gen height_gap_n = height_max - height_min if type == 1 | type == 2 
(49 missing values generated)

. replace height_gap_n = height_male - height_female  if type == 3
(49 real changes made)

. gen gap_ratio = height_gap/height_mean * 100

. 
. keep height_* height_mean gap_ratio age type birth_year hhid line wave taller_boy urban 

. duplicates drop 

Duplicates in terms of all variables

(0 observations are duplicates)

. * Combine the birth year groups 
. 
. gen age2 = age^2/100

. gen age_int = int(age)

. gen prov = int(hhid/1e7)

. 
. gen commid = int(hhid/1000)

. 
. ren prov province 

. gen birthyear = birth_year - 1 

. merge m:1 province birthyear using "fines.dta" 

    Result                           # of obs.
    -----------------------------------------
    not matched                           687
        from master                        34  (_merge==1)
        from using                        653  (_merge==2)

    matched                               141  (_merge==3)
    -----------------------------------------

. drop if _merge == 2 
(653 observations deleted)

. drop _merge 

. replace fine = 0 if birth_year <= 1979 & fine == . 
(8 real changes made)

. gen identical = type == 1 | type == 2 

. 
. ren fine fine_1 

. replace birthyear = birth_year - 1 
(0 real changes made)

. merge m:1 province birthyear using "fines.dta" 
(label provcnlbl already defined)

    Result                           # of obs.
    -----------------------------------------
    not matched                           687
        from master                        34  (_merge==1)
        from using                        653  (_merge==2)

    matched                               141  (_merge==3)
    -----------------------------------------

. drop if _merge == 2 
(653 observations deleted)

. drop _merge 

. replace fine = 0 if birth_year <= 1979 & fine == . 
(8 real changes made)

. ren fine fine_2

. * Define the effective fine rate 
. gen fine = 0.5*fine_1 + 0.5 * fine_2 
(26 missing values generated)

. * Combine the birth year groups
. recode birth_year (1979/1985= 1) (1986/1990 = 2)(1991/1995 = 3) (1996/2001 = 4) (2002/2006 = 5) (2007 / 2009 = 6), gen(bi
> rth_group)
(175 differences between birth_year and birth_group)

. * Provinces combination 
. gen cluster_id = prov 

. replace prov = 21 if prov == 23
(2 real changes made)

. replace prov = 42 if prov == 43 
(2 real changes made)

. replace prov = 45 if prov == 52
(4 real changes made)

. replace prov = 41 if prov == 37 
(13 real changes made)

. 
. duplicates drop

Duplicates in terms of all variables

(0 observations are duplicates)

. sort hhid wave 

. drop if hhid == hhid[_n-1] & wave == wave[_n-1] //drop duplicates households 
(88 observations deleted)

. 
. * Merge information from Mother 
. preserve 

. merge 1:m hhid line wave using "m10relatives"

    Result                           # of obs.
    -----------------------------------------
    not matched                       456,700
        from master                         0  (_merge==1)
        from using                    456,700  (_merge==2)

    matched                               362  (_merge==3)
    -----------------------------------------

. keep if _merge == 3
(456700 observations deleted)

. sort hhid wave

. keep if relation == 2
(278 observations deleted)

. keep o_hhid o_line

. ren o_hhid hhid

. ren o_line line 

. merge m:m hhid line using "m10pexam"

    Result                           # of obs.
    -----------------------------------------
    not matched                        94,656
        from master                         0  (_merge==1)
        from using                     94,656  (_merge==2)

    matched                               157  (_merge==3)
    -----------------------------------------

. keep if _merge == 3
(94656 observations deleted)

. keep hhid wave age 

. ren age mother_age

. save "mother_age",replace 
(note: file mother_age.dta not found)
file mother_age.dta saved

. restore 

. 
. sort hhid wave

. merge 1:m hhid wave using  "mother_age"

    Result                           # of obs.
    -----------------------------------------
    not matched                            83
        from master                         7  (_merge==1)
        from using                         76  (_merge==2)

    matched                                81  (_merge==3)
    -----------------------------------------

. drop if _merge == 2 
(76 observations deleted)

. drop _merge 

. 
. sort hhid wave 

. 
. drop if gap_ratio >= 8 & identical // outliers due to measures, by gr box  
(3 observations deleted)

. gen birth_age = mother_age - age 
(6 missing values generated)

. gen birth_mi = mi(birth_age)

. 
. sort prov birth_year 

. gen identXfine = identical * fine
(13 missing values generated)

. gen diffXfine = (1-identical) * fine
(13 missing values generated)

. 
. egen birth_age_mean = mean(birth_age) 

. replace birth_age = birth_age_mean if mi(birth_age) 
(6 real changes made)

. drop birth_age_mean

. 
. save "twins_chns_use",replace 
(note: file twins_chns_use.dta not found)
file twins_chns_use.dta saved

. 
. use "twins_chns_use", clear 

. /* Appendix Table A2 */
. su height_gap  height_mean gap_ratio 

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  height_gap |        85    2.094118    2.633862          0         13
 height_mean |        85    116.6212    28.47964      51.55      167.5
   gap_ratio |        85    1.741023       2.107          0   9.090909

. su height_gap  height_mean gap_ratio if identical 

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  height_gap |        60    1.293334    1.595637          0   7.199997
 height_mean |        60     117.005      28.101         60      163.6
   gap_ratio |        60    1.048139    1.198431          0   4.400976

. su height_gap  height_mean gap_ratio if !identical 

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
  height_gap |        25    4.016001      3.5455          0         13
 height_mean |        25       115.7    29.93827      51.55      167.5
   gap_ratio |        25    3.403945    2.815416          0   9.090909

. 
. /* Table 4 */
. gl control_fine_1 = "height_mean taller_boy urban age age2 birth_age i.birth_g i.prov i.wave"

. * Panel A
. reg height_gap fine identical $control_fine_1,  cluster(cluster_id)

Linear regression                                      Number of obs =      72
                                                       F(  6,     7) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.6310
                                                       Root MSE      =  2.0026

                             (Std. Err. adjusted for 8 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
  height_gap |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        fine |   1.834144   .3124577     5.87   0.001     1.095299    2.572989
   identical |   -3.46237   1.311766    -2.64   0.033    -6.564203   -.3605361
 height_mean |  -.0103916   .0538257    -0.19   0.852    -.1376693     .116886
  taller_boy |   1.189732   1.027698     1.16   0.285    -1.240389    3.619852
       urban |   .5580947   .9589408     0.58   0.579     -1.70944    2.825629
         age |  -.0656348   .7420535    -0.09   0.932    -1.820312    1.689043
        age2 |   1.090242   1.533332     0.71   0.500    -2.535512    4.715995
   birth_age |   .0383723   .1352535     0.28   0.785    -.2814514     .358196
             |
 birth_group |
          2  |   -.239422   .3098054    -0.77   0.465    -.9719954    .4931514
          3  |  -2.686928   1.966475    -1.37   0.214    -7.336901    1.963046
          4  |  -3.696416   3.506689    -1.05   0.327    -11.98842    4.595585
             |
    province |
         32  |   3.955466    .828912     4.77   0.002     1.995401    5.915532
         41  |   3.067929   1.111356     2.76   0.028     .4399904    5.695868
         42  |   4.739798   1.473825     3.22   0.015     1.254755    8.224841
         45  |   2.733973   .7525022     3.63   0.008     .9545875    4.513358
             |
        wave |
       1991  |   .4561634   .7454764     0.61   0.560    -1.306608    2.218935
       1993  |   .2924419   1.383169     0.21   0.839    -2.978234    3.563117
       1997  |   1.064476    1.60235     0.66   0.528    -2.724479     4.85343
       2000  |   .0092157   3.271613     0.00   0.998    -7.726919     7.74535
       2004  |   2.258209   4.606221     0.49   0.639    -8.633774    13.15019
       2006  |   2.821218   4.868494     0.58   0.580    -8.690941    14.33338
       2009  |   2.781857   5.680521     0.49   0.639    -10.65044    16.21415
             |
       _cons |   -1.31137   3.326279    -0.39   0.705     -9.17677     6.55403
------------------------------------------------------------------------------

. outreg2 using "table4.xls",replace keep(fine) dec(2)
table4.xls
dir : seeout

. reg height_gap identXfine diffXfine identical $control_fine_1 ,  cluster(cluster_id)

Linear regression                                      Number of obs =      72
                                                       F(  6,     7) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.6401
                                                       Root MSE      =  1.9985

                             (Std. Err. adjusted for 8 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
  height_gap |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  identXfine |   2.074592   .3797432     5.46   0.001     1.176642    2.972542
   diffXfine |   .7059038   .2397923     2.94   0.022      .138885    1.272923
   identical |  -5.361033   1.817817    -2.95   0.021    -9.659486    -1.06258
 height_mean |  -.0124039   .0488194    -0.25   0.807    -.1278434    .1030356
  taller_boy |   .8427483   1.260149     0.67   0.525    -2.137032    3.822528
       urban |   .5776197   1.008395     0.57   0.585    -1.806855    2.962095
         age |  -.0034551   .7343137    -0.00   0.996    -1.739831    1.732921
        age2 |   .7373386   1.455187     0.51   0.628    -2.703631    4.178308
   birth_age |     .06873   .1251688     0.55   0.600    -.2272471    .3647072
             |
 birth_group |
          2  |  -.1816497   .3301465    -0.55   0.599    -.9623222    .5990228
          3  |  -2.960976   2.376699    -1.25   0.253    -8.580975    2.659023
          4  |  -3.552143   4.476186    -0.79   0.454    -14.13664    7.032354
             |
    province |
         32  |   3.684536   .8083399     4.56   0.003     1.773116    5.595956
         41  |   2.876999    1.03517     2.78   0.027     .4292097    5.324788
         42  |   4.123442   1.594934     2.59   0.036     .3520228    7.894862
         45  |   2.550255   .6870815     3.71   0.008     .9255651    4.174944
             |
        wave |
       1991  |   .3603325   .7968528     0.45   0.665    -1.523925     2.24459
       1993  |   .2602597   1.552192     0.17   0.872     -3.41009     3.93061
       1997  |    1.06741   2.074405     0.51   0.623    -3.837778    5.972599
       2000  |   .0623672   3.998822     0.02   0.988    -9.393344    9.518078
       2004  |   2.097876   5.635552     0.37   0.721    -11.22809    15.42384
       2006  |   2.898786   5.792734     0.50   0.632    -10.79885    16.59642
       2009  |   2.847369   6.815763     0.42   0.689    -13.26935    18.96409
             |
       _cons |  -.2226625   3.077751    -0.07   0.944    -7.500387    7.055062
------------------------------------------------------------------------------

. outreg2 using "table4.xls",append keep(identXfine diffXfine) dec(2)
table4.xls
dir : seeout

. reg gap_ratio fine identical $control_fine_1,  cluster(cluster_id)

Linear regression                                      Number of obs =      72
                                                       F(  6,     7) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.6308
                                                       Root MSE      =   1.565

                             (Std. Err. adjusted for 8 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
   gap_ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        fine |   1.697664   .2293046     7.40   0.000     1.155444    2.239883
   identical |  -2.860944   1.219457    -2.35   0.051    -5.744502    .0226149
 height_mean |  -.0087499   .0371524    -0.24   0.821    -.0966013    .0791016
  taller_boy |   .9520361   1.146841     0.83   0.434    -1.759813    3.663885
       urban |   .6203712   .8631922     0.72   0.496    -1.420754    2.661497
         age |   -.123294   .6196783    -0.20   0.848      -1.5886    1.342012
        age2 |   .9451797   1.256597     0.75   0.476    -2.026199    3.916559
   birth_age |   .0055722   .1105606     0.05   0.961    -.2558621    .2670065
             |
 birth_group |
          2  |   .1860614   .2773624     0.67   0.524    -.4697966    .8419193
          3  |  -2.257591   2.156543    -1.05   0.330    -7.357006    2.841824
          4  |  -2.870339   3.802721    -0.75   0.475    -11.86234    6.121667
             |
    province |
         32  |    2.28394   .7701998     2.97   0.021     .4627067    4.105173
         41  |    2.06787   .9540355     2.17   0.067    -.1880658    4.323805
         42  |   3.601928    1.26957     2.84   0.025     .5998711    6.603984
         45  |   1.794154   .6307664     2.84   0.025     .3026288     3.28568
             |
        wave |
       1991  |   .2839779   .8169121     0.35   0.738    -1.647712    2.215668
       1993  |   .0967853   1.326731     0.07   0.944    -3.040436    3.234007
       1997  |   .6152346   1.852193     0.33   0.749    -3.764505    4.994974
       2000  |   .1671484   3.338998     0.05   0.961    -7.728327    8.062624
       2004  |   1.558028   4.736371     0.33   0.752    -9.641709    12.75777
       2006  |    2.18135   4.928807     0.44   0.671    -9.473426    13.83613
       2009  |   1.868007   5.617343     0.33   0.749     -11.4149    15.15091
             |
       _cons |   .4266816   2.697939     0.16   0.879     -5.95293    6.806293
------------------------------------------------------------------------------

. outreg2 using "table4.xls",append keep(fine) dec(2)
table4.xls
dir : seeout

. reg gap_ratio identXfine diffXfine identical $control_fine_1 ,  cluster(cluster_id)

Linear regression                                      Number of obs =      72
                                                       F(  6,     7) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.6322
                                                       Root MSE      =  1.5781

                             (Std. Err. adjusted for 8 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
   gap_ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  identXfine |    1.77219   .2632037     6.73   0.000     1.149812    2.394568
   diffXfine |   1.347968   .2525146     5.34   0.001     .7508655     1.94507
   identical |  -3.449431   1.619275    -2.13   0.071    -7.278409    .3795475
 height_mean |  -.0093736   .0358057    -0.26   0.801    -.0940406    .0752935
  taller_boy |   .8444893   1.280624     0.66   0.531    -2.183704    3.872683
       urban |    .626423    .885313     0.71   0.502     -1.46701    2.719856
         age |  -.1040215   .6199683    -0.17   0.871    -1.570014    1.361971
        age2 |   .8357981   1.246643     0.67   0.524    -2.112044     3.78364
   birth_age |   .0149815   .1073147     0.14   0.893    -.2387774    .2687404
             |
 birth_group |
          2  |   .2039678   .3087302     0.66   0.530    -.5260631    .9339987
          3  |  -2.342531    2.30239    -1.02   0.343     -7.78682    3.101757
          4  |  -2.825622   4.135267    -0.68   0.516    -12.60397    6.952731
             |
    province |
         32  |   2.199965   .7533752     2.92   0.022     .4185161    3.981415
         41  |   2.008691    .924271     2.17   0.066    -.1768623    4.194245
         42  |   3.410889   1.314692     2.59   0.036     .3021358    6.519643
         45  |   1.737211   .6156419     2.82   0.026     .2814496    3.192973
             |
        wave |
       1991  |   .2542754   .8285683     0.31   0.768    -1.704977    2.213528
       1993  |   .0868105    1.38947     0.06   0.952    -3.198765    3.372386
       1997  |   .6161442    2.02525     0.30   0.770     -4.17281    5.405099
       2000  |   .1836226   3.592956     0.05   0.961    -8.312369    8.679614
       2004  |   1.508334    5.09529     0.30   0.776    -10.54011    13.55678
       2006  |   2.205392   5.255482     0.42   0.687    -10.22185    14.63263
       2009  |   1.888313   6.012615     0.31   0.763    -12.32926    16.10589
             |
       _cons |   .7641244   2.739471     0.28   0.788    -5.713694    7.241943
------------------------------------------------------------------------------

. outreg2 using "table4.xls",append keep(identXfine diffXfine)  dec(2)
table4.xls
dir : seeout

. 
. 
. * Panel B
. sort hhid wave 

. drop if hhid == hhid[_n-1] // keep the only wave
(44 observations deleted)

. gl control_fine_2 = "height_mean taller_boy urban age age2 birth_age i.birth_g i.prov"

. reg height_gap fine identical $control_fine_2, cluster(cluster_id)

Linear regression                                      Number of obs =      33
                                                       F(  6,     7) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.7440
                                                       Root MSE      =  2.0707

                             (Std. Err. adjusted for 8 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
  height_gap |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        fine |   3.284753   1.079085     3.04   0.019     .7331209    5.836384
   identical |  -3.791631   1.986558    -1.91   0.098    -8.489095    .9058329
 height_mean |   .0942715   .1028205     0.92   0.390    -.1488604    .3374035
  taller_boy |   .6095743    1.85016     0.33   0.751     -3.76536    4.984508
       urban |  -.3374599   .5811406    -0.58   0.580    -1.711639    1.036719
         age |  -1.064271    .795718    -1.34   0.223    -2.945845    .8173029
        age2 |   5.477339   1.614408     3.39   0.012      1.65987    9.294808
   birth_age |  -.0073852   .1303077    -0.06   0.956     -.315514    .3007436
             |
 birth_group |
          2  |   1.928273   1.323766     1.46   0.189    -1.201935    5.058482
          3  |  -3.775561   .8154426    -4.63   0.002    -5.703776   -1.847346
          4  |  -5.263326    1.61541    -3.26   0.014    -9.083165   -1.443487
             |
    province |
         32  |    3.53485   1.347643     2.62   0.034       .34818     6.72152
         41  |   6.698737   1.610871     4.16   0.004     2.889634    10.50784
         42  |   7.795844   1.390224     5.61   0.001     4.508487     11.0832
         45  |   3.907037   1.487087     2.63   0.034     .3906341     7.42344
             |
       _cons |  -10.28591   6.794956    -1.51   0.174    -26.35342    5.781613
------------------------------------------------------------------------------

. outreg2 using "table4.xls",append keep(fine) dec(2)
table4.xls
dir : seeout

. reg height_gap identXfine diffXfine identical  $control_fine_2 ,  cluster(cluster_id)

Linear regression                                      Number of obs =      33
                                                       F(  6,     7) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.7448
                                                       Root MSE      =  2.1308

                             (Std. Err. adjusted for 8 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
  height_gap |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  identXfine |      3.368   1.565031     2.15   0.068    -.3327091     7.06871
   diffXfine |   2.937495   1.945746     1.51   0.175    -1.663464    7.538453
   identical |  -4.345991   4.800979    -0.91   0.395     -15.6985    7.006521
 height_mean |   .0984996   .0836637     1.18   0.278    -.0993335    .2963327
  taller_boy |   .5205348   1.783747     0.29   0.779    -3.697358    4.738427
       urban |  -.3300418   .5748236    -0.57   0.584    -1.689284      1.0292
         age |  -1.072713   .7481263    -1.43   0.195    -2.841751    .6963247
        age2 |   5.411519   1.990618     2.72   0.030      .704455    10.11858
   birth_age |  -.0036038   .1560502    -0.02   0.982     -.372604    .3653963
             |
 birth_group |
          2  |   2.046014   1.581096     1.29   0.237    -1.692684    5.784712
          3  |  -3.797445   .9069182    -4.19   0.004    -5.941966   -1.652924
          4  |  -5.127721   1.436358    -3.57   0.009    -8.524167   -1.731275
             |
    province |
         32  |   3.520085   1.423328     2.47   0.043     .1544485    6.885721
         41  |   6.736491   1.505703     4.47   0.003     3.176068    10.29691
         42  |   7.711166   1.942481     3.97   0.005     3.117928     12.3044
         45  |   3.907318   1.526451     2.56   0.038     .2978347    7.516802
             |
       _cons |  -10.33396    6.91287    -1.49   0.179     -26.6803    6.012378
------------------------------------------------------------------------------

. outreg2 using "table4.xls",append keep(identXfine diffXfine) dec(2)
table4.xls
dir : seeout

. 
. reg gap_ratio fine identical  $control_fine_2, cluster(cluster_id)

Linear regression                                      Number of obs =      33
                                                       F(  6,     7) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.7655
                                                       Root MSE      =   1.606

                             (Std. Err. adjusted for 8 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
   gap_ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        fine |   2.708583   .5860731     4.62   0.002      1.32274    4.094425
   identical |  -3.208288   1.755069    -1.83   0.110    -7.358366    .9417902
 height_mean |   .0760096    .093561     0.81   0.443    -.1452271    .2972463
  taller_boy |   .5193659   1.769255     0.29   0.778    -3.664258     4.70299
       urban |   .0064382   .5121763     0.01   0.990    -1.204666    1.217543
         age |  -.9731695   .6999441    -1.39   0.207    -2.628274    .6819354
        age2 |   4.596206   1.469952     3.13   0.017     1.120322    8.072091
   birth_age |  -.0198513   .1203602    -0.16   0.874    -.3044579    .2647553
             |
 birth_group |
          2  |   1.946944   1.168508     1.67   0.140    -.8161377    4.710025
          3  |  -3.160724   .6952684    -4.55   0.003    -4.804773   -1.516676
          4  |    -3.9479   1.184186    -3.33   0.013    -6.748055   -1.147745
             |
    province |
         32  |   1.914266   1.075491     1.78   0.118    -.6288669    4.457399
         41  |   4.769007   1.455199     3.28   0.014     1.328009    8.210006
         42  |   6.234324   1.350771     4.62   0.002     3.040258     9.42839
         45  |   2.796681   1.243033     2.25   0.059    -.1426258    5.735987
             |
       _cons |  -6.811008   6.379882    -1.07   0.321    -21.89703    8.275017
------------------------------------------------------------------------------

. outreg2 using "table4.xls",append keep(fine) dec(2)
table4.xls
dir : seeout

. reg gap_ratio identXfine diffXfine identical $control_fine_2 ,  cluster(cluster_id)

Linear regression                                      Number of obs =      33
                                                       F(  6,     7) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.7684
                                                       Root MSE      =  1.6452

                             (Std. Err. adjusted for 8 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
   gap_ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  identXfine |   2.584243   .8358254     3.09   0.018       .60783    4.560656
   diffXfine |   3.227253   1.157763     2.79   0.027     .4895779    5.964927
   identical |  -2.380287    3.05565    -0.78   0.462    -9.605751    4.845177
 height_mean |   .0696946   .0845644     0.82   0.437    -.1302685    .2696577
  taller_boy |   .6523566   1.675353     0.39   0.709    -3.309224    4.613937
       urban |  -.0046416   .5022346    -0.01   0.993    -1.192238    1.182955
         age |   -.960561   .7275817    -1.32   0.228    -2.681018    .7598964
        age2 |   4.694517   1.889103     2.49   0.042     .2274982    9.161536
   birth_age |  -.0254993   .1334516    -0.19   0.854    -.3410621    .2900635
             |
 birth_group |
          2  |   1.771085   1.154248     1.53   0.169    -.9582786    4.500448
          3  |  -3.128038   .7079068    -4.42   0.003    -4.801971   -1.454104
          4  |  -4.150441   1.054275    -3.94   0.006    -6.643406   -1.657476
             |
    province |
         32  |    1.93632    1.25351     1.54   0.166    -1.027761    4.900401
         41  |   4.712619   1.440478     3.27   0.014     1.306429    8.118808
         42  |   6.360801    1.72265     3.69   0.008     2.287381    10.43422
         45  |   2.796261   1.297496     2.16   0.068    -.2718288     5.86435
             |
       _cons |  -6.739228   6.398732    -1.05   0.327    -21.86982    8.391367
------------------------------------------------------------------------------

. outreg2 using "table4.xls",append keep(identXfine diffXfine) dec(2)
table4.xls
dir : seeout

. 
. cap erase "mother_age.dta"

. cap erase "twins_chns_use.dta"

. 
. 
. 
. 
. *** Figure 1 and Figure 2 ***
. use "twins_order_data_reg", clear

. set scheme s2mono

. * Figure 1
. preserve 

. collapse twins [aw = weight], by(birth_year)

. tw scatter twins birth_year, xtit(Year of birth) xlabel(1965(5)2005) ytit("Birth rate (%)") ///
> note("Data source is 1982, 1990, 2000 and 2005 Census.") ylabel(0.2(0.1)0.9) xline(1979, lp(dash) ) 

. restore 

. 
. * Figure 2
. preserve 

. collapse twins [aw = weight], by(birth_year h_fm_han)

. reshape wide twins, i(birth_year) j(h_fm_han)
(note: j = 0 1)

Data                               long   ->   wide
-----------------------------------------------------------------------------
Number of obs.                       82   ->      41
Number of variables                   3   ->       3
j variable (2 values)          h_fm_han   ->   (dropped)
xij variables:
                                  twins   ->   twins0 twins1
-----------------------------------------------------------------------------

. cap drop twins1_l twins0_l

. lowess twins1 birth_year if birth_year >= 1971 & birth_year <= 2003, gen(twins1_l) nograph

. lowess twins0 birth_year if birth_year >= 1971 & birth_year <= 2003, gen(twins0_l) nograph

. 
. tw (scatter twins1 twins0 birth_year, xtit(Year of birth) xlabel(1965(5)2005) ytit("Birth rate (%)") ///
> note("Data source is 1982, 1990, 2000 and 2005 Census.") ylabel(0.2(0.1)0.9) xline(1979, lp(dash) ) ///
>  legend(label(1 Han) label(2 Minority) label(3 Han smooth) label(4 Minority smooth))) ///
> (line twins1_l twins0_l birth_year)

. restore 

. 
. * Appendix Figure A1 ***
. use "fines",clear 
(Year X Province fertility policy data)

. drop if province == 54
(22 observations deleted)

. ren birthyear year 

. 
. tw line fine year, by(province)

. 
. ** Appendix Table B1 *****
. 
. use "twins_order_data_reg", clear

. cap drop fine_* 

. gen province = prov 

. forvalues i = 1(2)5{
  2. gen birthyear = birth_year +`i'
  3. merge m:1 province birthyear using "fines", keepusing(fine) 
  4. ren fine fine_`i'
  5. drop if _merge == 2
  6. drop _merge 
  7. drop birthyear
  8. }

    Result                           # of obs.
    -----------------------------------------
    not matched                     1,591,909
        from master                 1,591,843  (_merge==1)
        from using                         66  (_merge==2)

    matched                         4,516,098  (_merge==3)
    -----------------------------------------
(66 observations deleted)
(label provcnlbl already defined)

    Result                           # of obs.
    -----------------------------------------
    not matched                     1,338,678
        from master                 1,338,612  (_merge==1)
        from using                         66  (_merge==2)

    matched                         4,769,329  (_merge==3)
    -----------------------------------------
(66 observations deleted)
(label provcnlbl already defined)

    Result                           # of obs.
    -----------------------------------------
    not matched                     1,173,803
        from master                 1,173,737  (_merge==1)
        from using                         66  (_merge==2)

    matched                         4,934,204  (_merge==3)
    -----------------------------------------
(66 observations deleted)

. replace birth_month = 0 if mi(birth_month)
(1710130 real changes made)

. keep if birth_year > 1980
(2215786 observations deleted)

. 
. gl control_test = "rural h_fm_han i.order i.m_birth_age i.birth_month i.prov i.cell prov*Xyob"

. 
. replace twins = twins/100 
(25953 real changes made)

. * Appendix Table B1
. reg fine_1 twins $control_test [aw = weight], cluster(cluster_id)
(sum of wgt is   4.6155e+06)
note: 70.cell omitted because of collinearity

Linear regression                                      Number of obs = 3846779
                                                       F( 26,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.7537
                                                       Root MSE      =  .46963

                            (Std. Err. adjusted for 28 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
      fine_1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       twins |   .0134573   .0080513     1.67   0.106    -.0030626    .0299773
       rural |    -.00355   .0031208    -1.14   0.265    -.0099533    .0028532
    h_fm_han |   .0142568   .0115252     1.24   0.227    -.0093909    .0379045
             |
       order |
          2  |   .0075016   .0048926     1.53   0.137    -.0025372    .0175404
          3  |   .0240875   .0100396     2.40   0.024      .003488    .0446871
             |
 m_birth_age |
         17  |  -.0032304   .0096825    -0.33   0.741    -.0230974    .0166365
         18  |   .0037193   .0102767     0.36   0.720    -.0173668    .0248054
         19  |   .0022215   .0097682     0.23   0.822    -.0178211    .0222642
         20  |   .0053709   .0092414     0.58   0.566     -.013591    .0243328
         21  |   .0064539   .0096963     0.67   0.511    -.0134413    .0263491
         22  |    .007772   .0093586     0.83   0.414    -.0114304    .0269743
         23  |   .0067771   .0099983     0.68   0.504    -.0137377    .0272919
         24  |   .0033354   .0105268     0.32   0.754    -.0182637    .0249345
         25  |  -.0001157    .011275    -0.01   0.992    -.0232501    .0230186
         26  |   -.003545   .0130728    -0.27   0.788    -.0303681    .0232781
         27  |   -.003686   .0133748    -0.28   0.785    -.0311289    .0237568
         28  |  -.0005817   .0137328    -0.04   0.967     -.028759    .0275956
         29  |   .0120145   .0136256     0.88   0.386    -.0159428    .0399718
         30  |   .0028034   .0130828     0.21   0.832    -.0240404    .0296472
         31  |  -.0005797   .0130146    -0.04   0.965    -.0272834     .026124
         32  |    .004043   .0128744     0.31   0.756    -.0223732    .0304591
         33  |   .0062957   .0152271     0.41   0.683    -.0249477    .0375391
         34  |  -.0019393   .0165979    -0.12   0.908    -.0359954    .0321167
         35  |  -.0077905     .02147    -0.36   0.720    -.0518434    .0362623
         36  |  -.0214839   .0185802    -1.16   0.258    -.0596072    .0166395
         37  |   .0283777   .0218361     1.30   0.205    -.0164264    .0731817
         38  |   .0013475   .0187243     0.07   0.943    -.0370716    .0397667
         39  |  -.0045063   .0280932    -0.16   0.874    -.0621487    .0531361
         40  |   .0129071   .0283443     0.46   0.652    -.0452507    .0710648
         41  |    .007092   .0338751     0.21   0.836     -.062414     .076598
         42  |   .0688859   .0506573     1.36   0.185    -.0350543     .172826
         43  |   .0901008   .0475859     1.89   0.069    -.0075374    .1877391
         44  |  -.0022801   .0381428    -0.06   0.953    -.0805426    .0759824
         45  |  -.0210493   .0527611    -0.40   0.693    -.1293062    .0872075
         46  |  -.0475539   .0379811    -1.25   0.221    -.1254846    .0303768
         47  |   .1305382   .1200273     1.09   0.286    -.1157375    .3768138
         48  |  -.0554212   .1457732    -0.38   0.707    -.3545231    .2436808
         49  |  -.0339202   .0647273    -0.52   0.605    -.1667298    .0988893
         50  |   .0801573   .0835908     0.96   0.346    -.0913569    .2516715
             |
 birth_month |
          1  |   5.471482    .120154    45.54   0.000     5.224946    5.718018
          2  |   5.468378    .119013    45.95   0.000     5.224183    5.712573
          3  |   5.469144   .1189693    45.97   0.000     5.225039    5.713249
          4  |   5.469013   .1188488    46.02   0.000     5.225156    5.712871
          5  |   5.467721   .1192851    45.84   0.000     5.222969    5.712474
          6  |   5.465832    .118752    46.03   0.000     5.222173    5.709491
          7  |   5.466744   .1184014    46.17   0.000     5.223804    5.709683
          8  |   5.466812   .1182955    46.21   0.000      5.22409    5.709534
          9  |   5.465507   .1180012    46.32   0.000     5.223389    5.707625
         10  |   5.467448   .1182421    46.24   0.000     5.224835    5.710061
         11  |   5.468225   .1190381    45.94   0.000     5.223979    5.712471
         12  |   5.469622   .1193404    45.83   0.000     5.224756    5.714488
             |
        prov |
         12  |   7.392704   .0287546   257.10   0.000     7.333704    7.451703
         13  |   4.894731   .0336096   145.64   0.000      4.82577    4.963692
         14  |   6.892706   .0341248   201.99   0.000     6.822687    6.962724
         15  |   5.945598   .0134671   441.49   0.000     5.917966     5.97323
         21  |   1.352755   .0309531    43.70   0.000     1.289245    1.416266
         22  |   8.223464   .0249466   329.64   0.000     8.172277     8.27465
         23  |   6.840552   .0276926   247.02   0.000     6.783731    6.897372
         31  |   2.327228   .0121807   191.06   0.000     2.302236    2.352221
         32  |   3.381167   .0469823    71.97   0.000     3.284767    3.477567
         33  |    3.77998    .020708   182.54   0.000      3.73749    3.822469
         34  |   6.353062   .0336628   188.73   0.000     6.283992    6.422133
         35  |   2.983539    .030406    98.12   0.000     2.921151    3.045927
         36  |   5.494529   .0243915   225.26   0.000     5.444481    5.544576
         37  |   7.270465   .0127273   571.25   0.000     7.244351    7.296579
         41  |   5.296943   .0182511   290.23   0.000     5.259495    5.334391
         42  |   4.262625   .0413866   103.00   0.000     4.177707    4.347544
         43  |   3.885461   .0272868   142.39   0.000     3.829474    3.941449
         44  |   3.416122   .0468985    72.84   0.000     3.319894    3.512349
         45  |   2.047326   .0228224    89.71   0.000     2.000498    2.094153
         51  |   5.496384   .0299716   183.39   0.000     5.434888    5.557881
         52  |   3.954624   .0378663   104.44   0.000     3.876929     4.03232
         53  |   4.000351   .0570297    70.15   0.000     3.883336    4.117367
         61  |   4.627957    .037162   124.53   0.000     4.551707    4.704207
         62  |   5.490244   .0565735    97.05   0.000     5.374165    5.606323
         63  |   5.095859   .0630141    80.87   0.000     4.966565    5.225154
         64  |   3.563201   .0664664    53.61   0.000     3.426824    3.699579
         65  |   2.970565   .0379904    78.19   0.000     2.892615    3.048515
             |
        cell |
         18  |   .1019528   .0493295     2.07   0.048      .000737    .2031686
         28  |   -5.46153   .1211725   -45.07   0.000    -5.710156   -5.212905
         29  |  -5.377662   .1012313   -53.12   0.000    -5.585371   -5.169952
         30  |  -5.157506    .094421   -54.62   0.000    -5.351242   -4.963771
         31  |  -4.986743   .1058569   -47.11   0.000    -5.203943   -4.769542
         32  |  -4.767103   .1082725   -44.03   0.000     -4.98926   -4.544947
         33  |  -4.571075   .1112511   -41.09   0.000    -4.799343   -4.342806
         34  |   -4.28235   .0927766   -46.16   0.000    -4.472712   -4.091988
         35  |  -4.071552   .1007119   -40.43   0.000    -4.278196   -3.864909
         36  |   -3.61152   .1635169   -22.09   0.000    -3.947029   -3.276011
         37  |  -3.111251   .1881822   -16.53   0.000     -3.49737   -2.725133
         38  |  -5.380718   .1053532   -51.07   0.000    -5.596885   -5.164551
         39  |  -5.159706   .0969636   -53.21   0.000    -5.358659   -4.960753
         40  |  -4.979625   .1005258   -49.54   0.000    -5.185887   -4.773363
         41  |  -4.751793   .0988256   -48.08   0.000    -4.954567    -4.54902
         42  |  -4.549552   .0984164   -46.23   0.000    -4.751486   -4.347619
         43  |  -4.288346   .0925711   -46.32   0.000    -4.478286   -4.098405
         44  |  -4.073461   .1013359   -40.20   0.000    -4.281385   -3.865537
         45  |  -3.622328   .1595306   -22.71   0.000    -3.949658   -3.294998
         46  |  -3.077911   .1879156   -16.38   0.000    -3.463482    -2.69234
         47  |  -2.628733   .1953212   -13.46   0.000    -3.029499   -2.227967
         48  |  -2.152896   .2062321   -10.44   0.000    -2.576049   -1.729743
         49  |  -1.942188   .2052948    -9.46   0.000    -2.363418   -1.520958
         50  |  -1.579237   .1845816    -8.56   0.000    -1.957967   -1.200507
         51  |   -1.34355   .1861558    -7.22   0.000    -1.725511   -.9615903
         52  |  -1.125905   .1836174    -6.13   0.000    -1.502657   -.7491537
         53  |   -.798631   .1703187    -4.69   0.000    -1.148096    -.449166
         54  |  -.3735552   .0603815    -6.19   0.000    -.4974479   -.2496625
         55  |  -.1698433   .0462971    -3.67   0.001    -.2648372   -.0748495
         56  |   .0479652   .0424915     1.13   0.269    -.0392203    .1351506
         57  |  -4.297113   .1035976   -41.48   0.000    -4.509678   -4.084549
         58  |  -4.105845   .1046558   -39.23   0.000    -4.320581   -3.891109
         59  |  -3.695394   .1458338   -25.34   0.000     -3.99462   -3.396167
         60  |  -3.190119   .1858959   -17.16   0.000    -3.571546   -2.808692
         61  |  -2.717481   .2223426   -12.22   0.000     -3.17369   -2.261271
         62  |  -2.035775   .2100221    -9.69   0.000    -2.466704   -1.604845
         63  |  -1.820837   .2043764    -8.91   0.000    -2.240183   -1.401491
         64  |  -1.520189   .1782753    -8.53   0.000    -1.885979   -1.154398
         65  |  -1.267409   .1829703    -6.93   0.000    -1.642834   -.8919853
         66  |   -1.05704   .1767229    -5.98   0.000    -1.419645   -.6944341
         67  |  -.7649068   .1528688    -5.00   0.000    -1.078568   -.4512459
         68  |  -.4060684   .0322673   -12.58   0.000    -.4722755   -.3398612
         69  |  -.2058628   .0167774   -12.27   0.000    -.2402871   -.1714385
         70  |          0  (omitted)
             |
   prov2Xyob |  -.3413786   .0010478  -325.79   0.000    -.3435286   -.3392286
   prov3Xyob |  -.2091649   .0015268  -137.00   0.000    -.2122976   -.2060322
   prov4Xyob |  -.3130513   .0014247  -219.73   0.000    -.3159746   -.3101281
   prov5Xyob |  -.2715146   .0005234  -518.76   0.000    -.2725885   -.2704407
   prov6Xyob |   -.046576   .0013205   -35.27   0.000    -.0492854   -.0438667
   prov7Xyob |  -.3891023   .0011396  -341.43   0.000    -.3914406    -.386764
   prov8Xyob |  -.3131653   .0011836  -264.58   0.000    -.3155939   -.3107367
   prov9Xyob |  -.1336262   .0004454  -300.04   0.000      -.13454   -.1327123
  prov10Xyob |  -.1508709   .0021813   -69.17   0.000    -.1553465   -.1463953
  prov11Xyob |  -.1802527   .0008695  -207.31   0.000    -.1820367   -.1784687
  prov12Xyob |  -.3168597    .001452  -218.22   0.000     -.319839   -.3138804
  prov13Xyob |  -.1418446   .0013548  -104.70   0.000    -.1446244   -.1390647
  prov14Xyob |   -.250653   .0009768  -256.60   0.000    -.2526573   -.2486487
  prov15Xyob |  -.3309998   .0005169  -640.31   0.000    -.3320605   -.3299391
  prov16Xyob |  -.2439609   .0008406  -290.23   0.000    -.2456856   -.2422361
  prov17Xyob |  -.1910698   .0019189   -99.57   0.000     -.195007   -.1871326
  prov18Xyob |  -.1929752   .0013025  -148.15   0.000    -.1956478   -.1903026
  prov19Xyob |  -.1474878   .0019625   -75.15   0.000    -.1515146   -.1434611
  prov20Xyob |  -.0856611   .0008259  -103.71   0.000    -.0873557   -.0839664
  prov21Xyob |  -.2588372   .0013632  -189.87   0.000    -.2616344   -.2560401
  prov22Xyob |  -.1857903   .0014462  -128.47   0.000    -.1887577   -.1828229
  prov23Xyob |  -.1886009   .0021091   -89.42   0.000    -.1929285   -.1842733
  prov24Xyob |  -.2298811     .00158  -145.50   0.000     -.233123   -.2266393
  prov25Xyob |  -.2493552   .0022501  -110.82   0.000     -.253972   -.2447384
  prov26Xyob |  -.2527084   .0022716  -111.25   0.000    -.2573695   -.2480474
  prov27Xyob |  -.1395261   .0024019   -58.09   0.000    -.1444545   -.1345977
  prov28Xyob |  -.1281935   .0013767   -93.11   0.000    -.1310184   -.1253687
       _cons |   .0904853   .0703367     1.29   0.209    -.0538338    .2348044
------------------------------------------------------------------------------

. outreg2 using "table_b1.xls", keep( twins) replace dec(3)
table_b1.xls
dir : seeout

. reg fine_3 twins $control_test [aw = weight], cluster(cluster_id)
(sum of wgt is   4.2336e+06)
note: 67.cell omitted because of collinearity

Linear regression                                      Number of obs = 3617399
                                                       F( 27,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.7784
                                                       Root MSE      =  .48912

                            (Std. Err. adjusted for 28 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
      fine_3 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       twins |   .0049415   .0053755     0.92   0.366    -.0060881    .0159711
       rural |   .0024816   .0042097     0.59   0.560    -.0061559    .0111191
    h_fm_han |   .0050227   .0031402     1.60   0.121    -.0014204    .0114658
             |
       order |
          2  |   .0036911   .0043952     0.84   0.408    -.0053271    .0127092
          3  |   .0135394   .0111584     1.21   0.235    -.0093557    .0364345
             |
 m_birth_age |
         17  |    .000315   .0057441     0.05   0.957    -.0114708    .0121009
         18  |   .0049937   .0078529     0.64   0.530    -.0111192    .0211066
         19  |   .0079285    .008166     0.97   0.340    -.0088268    .0246838
         20  |    .004456   .0077626     0.57   0.571    -.0114716    .0203835
         21  |    .007593   .0088068     0.86   0.396    -.0104771    .0256631
         22  |   .0060205   .0086133     0.70   0.491    -.0116527    .0236936
         23  |   .0000797   .0082212     0.01   0.992    -.0167888    .0169483
         24  |  -.0049177   .0088928    -0.55   0.585    -.0231642    .0133288
         25  |  -.0029843    .009099    -0.33   0.745    -.0216539    .0156853
         26  |  -.0026798   .0091372    -0.29   0.772    -.0214278    .0160681
         27  |  -.0012611    .010296    -0.12   0.903    -.0223868    .0198646
         28  |  -.0032898   .0105255    -0.31   0.757    -.0248864    .0183067
         29  |   -.003887    .011967    -0.32   0.748    -.0284411    .0206672
         30  |   .0018807   .0114399     0.16   0.871    -.0215919    .0253533
         31  |    -.00461   .0126759    -0.36   0.719    -.0306189    .0213989
         32  |  -.0043209   .0105748    -0.41   0.686    -.0260186    .0173769
         33  |   .0135089   .0136452     0.99   0.331    -.0144887    .0415066
         34  |   .0044116   .0142446     0.31   0.759    -.0248158     .033639
         35  |  -.0055714   .0184305    -0.30   0.765    -.0433876    .0322447
         36  |  -.0283879   .0135091    -2.10   0.045    -.0561063   -.0006694
         37  |  -.0222148   .0120268    -1.85   0.076    -.0468918    .0024622
         38  |   .0218872   .0217605     1.01   0.323    -.0227617    .0665362
         39  |  -.0339581   .0267144    -1.27   0.215    -.0887715    .0208554
         40  |    .035462   .0214023     1.66   0.109    -.0084518    .0793758
         41  |   .0331059   .0251287     1.32   0.199    -.0184539    .0846657
         42  |   .0062362   .0311303     0.20   0.843    -.0576379    .0701102
         43  |   .0315817   .0396503     0.80   0.433     -.049774    .1129375
         44  |  -.0297058   .0637065    -0.47   0.645    -.1604207    .1010091
         45  |  -.0486193   .0619306    -0.79   0.439    -.1756903    .0784518
         46  |   .0873806    .076061     1.15   0.261    -.0686838    .2434449
         47  |   .0570573   .0471712     1.21   0.237    -.0397299    .1538446
         48  |  -.0383799    .123303    -0.31   0.758    -.2913768    .2146169
         49  |  -.0233218   .0969125    -0.24   0.812    -.2221698    .1755262
         50  |  -.1246246   .0712021    -1.75   0.091    -.2707193    .0214701
             |
 birth_month |
          1  |   5.828379    .124777    46.71   0.000     5.572358      6.0844
          2  |   5.828944   .1247051    46.74   0.000      5.57307    6.084817
          3  |   5.831292   .1241082    46.99   0.000     5.576643    6.085941
          4  |   5.828874   .1250671    46.61   0.000     5.572258    6.085491
          5  |   5.830567   .1248337    46.71   0.000      5.57443    6.086705
          6  |    5.83092    .124829    46.71   0.000     5.574792    6.087048
          7  |    5.82981   .1245852    46.79   0.000     5.574182    6.085438
          8  |   5.833576   .1241053    47.01   0.000     5.578933    6.088219
          9  |   5.832712   .1240408    47.02   0.000     5.578201    6.087223
         10  |   5.830924   .1239731    47.03   0.000     5.576552    6.085296
         11  |   5.831316    .124279    46.92   0.000     5.576316    6.086316
         12  |   5.833138   .1240932    47.01   0.000      5.57852    6.087756
             |
        prov |
         12  |   7.877824     .02858   275.64   0.000     7.819183    7.936465
         13  |   5.971047   .0470291   126.96   0.000     5.874552    6.067543
         14  |    7.62961   .0428543   178.04   0.000      7.54168    7.717539
         15  |   6.400076   .0087878   728.29   0.000     6.382045    6.418107
         21  |   1.101358   .0206033    53.46   0.000     1.059083    1.143632
         22  |   8.653596   .0265558   325.86   0.000     8.599108    8.708084
         23  |   7.664419   .0289278   264.95   0.000     7.605064    7.723774
         31  |   2.010981   .0135394   148.53   0.000       1.9832    2.038761
         32  |   4.143326   .0326867   126.76   0.000     4.076258    4.210393
         33  |   4.844439   .0107897   448.99   0.000     4.822301    4.866578
         34  |   6.985847   .0345027   202.47   0.000     6.915054    7.056641
         35  |   3.459029   .0344034   100.54   0.000     3.388439    3.529619
         36  |   5.573896   .0258961   215.24   0.000     5.520762    5.627031
         37  |   8.095845   .0153889   526.08   0.000      8.06427    8.127421
         41  |   5.990607   .0301031   199.00   0.000     5.928841    6.052374
         42  |   4.548796   .0478591    95.05   0.000     4.450597    4.646994
         43  |   4.886513   .0427315   114.35   0.000     4.798835    4.974191
         44  |   3.862805   .0652361    59.21   0.000     3.728952    3.996659
         45  |   1.581367    .024638    64.18   0.000     1.530814     1.63192
         51  |   5.409188   .0209515   258.18   0.000     5.366199    5.452177
         52  |   3.152519   .0535881    58.83   0.000     3.042566    3.262473
         53  |   4.516846   .0738205    61.19   0.000     4.365379    4.668313
         61  |   5.396147   .0406461   132.76   0.000     5.312748    5.479546
         62  |   6.269036   .0706007    88.80   0.000     6.124176    6.413897
         63  |   5.298648   .0818087    64.77   0.000     5.130791    5.466506
         64  |   4.689292   .0786182    59.65   0.000     4.527981    4.850603
         65  |   3.464808   .0457873    75.67   0.000     3.370861    3.558756
             |
        cell |
         18  |   .2806476   .0249322    11.26   0.000      .229491    .3318043
         28  |   -5.84164   .1244906   -46.92   0.000    -6.097073   -5.586206
         29  |  -5.557374    .111655   -49.77   0.000    -5.786472   -5.328277
         30  |  -5.283657   .0968101   -54.58   0.000    -5.482295   -5.085019
         31  |  -4.964478   .0902082   -55.03   0.000     -5.14957   -4.779386
         32  |  -4.688307   .0971902   -48.24   0.000    -4.887725   -4.488889
         33  |  -4.173362   .1449109   -28.80   0.000    -4.470694   -3.876029
         34  |  -3.619824   .1738625   -20.82   0.000     -3.97656   -3.263087
         35  |  -3.083677   .1785311   -17.27   0.000    -3.449992   -2.717361
         36  |  -2.557564   .2077131   -12.31   0.000    -2.983756   -2.131372
         37  |  -2.279174   .2014823   -11.31   0.000    -2.692581   -1.865766
         38  |  -5.567181   .1113993   -49.98   0.000    -5.795753   -5.338608
         39  |  -5.291562   .0978062   -54.10   0.000    -5.492244    -5.09088
         40  |  -4.969799    .091299   -54.43   0.000    -5.157129   -4.782468
         41  |   -4.69843   .0968111   -48.53   0.000     -4.89707    -4.49979
         42  |  -4.184846   .1427552   -29.31   0.000    -4.477756   -3.891937
         43  |  -3.603899   .1719388   -20.96   0.000    -3.956689    -3.25111
         44  |  -3.081192   .1767322   -17.43   0.000    -3.443817   -2.718568
         45  |  -2.537364   .2058687   -12.33   0.000    -2.959772   -2.114957
         46  |  -2.279828   .2030805   -11.23   0.000    -2.696514   -1.863141
         47  |  -1.866489   .1875691    -9.95   0.000    -2.251349   -1.481629
         48  |  -1.570497   .1821654    -8.62   0.000     -1.94427   -1.196725
         49  |    -1.3018   .1771925    -7.35   0.000    -1.665369   -.9382308
         50  |  -.9420276   .1621986    -5.81   0.000    -1.274832   -.6092236
         51  |  -.5017208   .0603693    -8.31   0.000    -.6255884   -.3778533
         52  |  -.2204204   .0469193    -4.70   0.000    -.3166908   -.1241501
         53  |   .0632395   .0420215     1.50   0.144    -.0229814    .1494604
         57  |  -3.730084   .1678784   -22.22   0.000    -4.074542   -3.385626
         58  |  -3.188914    .189465   -16.83   0.000    -3.577664   -2.800164
         59  |   -2.41458   .2162988   -11.16   0.000    -2.858389   -1.970772
         60  |  -2.156215   .2098879   -10.27   0.000    -2.586869    -1.72556
         61  |  -1.807835   .1891155    -9.56   0.000    -2.195868   -1.419802
         62  |  -1.516083   .1780443    -8.52   0.000    -1.881399   -1.150766
         63  |  -1.250053    .167694    -7.45   0.000    -1.594133   -.9059732
         64  |  -.9276061   .1427338    -6.50   0.000    -1.220472   -.6347405
         65  |  -.5449082   .0444512   -12.26   0.000    -.6361145   -.4537019
         66  |  -.2722406   .0208737   -13.04   0.000      -.31507   -.2294113
         67  |          0  (omitted)
             |
   prov2Xyob |   -.410256   .0012004  -341.75   0.000    -.4127191   -.4077929
   prov3Xyob |   -.284572   .0020929  -135.97   0.000    -.2888663   -.2802778
   prov4Xyob |   -.387524   .0018364  -211.03   0.000    -.3912918   -.3837561
   prov5Xyob |  -.3317392   .0003111 -1066.22   0.000    -.3323776   -.3311008
   prov6Xyob |  -.0507637   .0008746   -58.04   0.000    -.0525582   -.0489692
   prov7Xyob |  -.4622397   .0011621  -397.76   0.000    -.4646241   -.4598552
   prov8Xyob |  -.3927167   .0012014  -326.89   0.000    -.3951817   -.3902517
   prov9Xyob |  -.1454702   .0005742  -253.32   0.000    -.1466485    -.144292
  prov10Xyob |  -.2042476   .0015393  -132.69   0.000     -.207406   -.2010891
  prov11Xyob |  -.2507378   .0003289  -762.44   0.000    -.2514126    -.250063
  prov12Xyob |  -.3888376   .0014031  -277.14   0.000    -.3917164   -.3859587
  prov13Xyob |   -.183431   .0014279  -128.46   0.000    -.1863608   -.1805013
  prov14Xyob |  -.2947673   .0009308  -316.67   0.000    -.2966772   -.2928574
  prov15Xyob |  -.4128215   .0006238  -661.80   0.000    -.4141014   -.4115416
  prov16Xyob |  -.3076936   .0013197  -233.16   0.000    -.3104014   -.3049859
  prov17Xyob |  -.2300549   .0021325  -107.88   0.000    -.2344303   -.2256794
  prov18Xyob |  -.2630849   .0019766  -133.10   0.000    -.2671406   -.2590293
  prov19Xyob |  -.1893749   .0028058   -67.49   0.000    -.1951318   -.1836179
  prov20Xyob |  -.0926027   .0008143  -113.73   0.000    -.0942734    -.090932
  prov21Xyob |   -.299008   .0007221  -414.08   0.000    -.3004896   -.2975264
  prov22Xyob |  -.1864881   .0023076   -80.81   0.000    -.1912229   -.1817533
  prov23Xyob |  -.2381032   .0031135   -76.47   0.000    -.2444916   -.2317148
  prov24Xyob |  -.2946805   .0016735  -176.08   0.000    -.2981144   -.2912467
  prov25Xyob |  -.3182264   .0028879  -110.19   0.000    -.3241518    -.312301
  prov26Xyob |  -.2995646   .0032984   -90.82   0.000    -.3063324   -.2927968
  prov27Xyob |  -.2071224   .0032591   -63.55   0.000    -.2138094   -.2004353
  prov28Xyob |  -.1686662   .0019429   -86.81   0.000    -.1726527   -.1646798
       _cons |   .3403484   .0737144     4.62   0.000      .189099    .4915979
------------------------------------------------------------------------------

. outreg2 using "table_b1.xls", keep( twins) append dec(3)
table_b1.xls
dir : seeout

. reg fine_5 twins $control_test [aw = weight], cluster(cluster_id)
(sum of wgt is   3.9082e+06)
note: 65.cell omitted because of collinearity

Linear regression                                      Number of obs = 3412641
                                                       F( 27,    27) =       .
                                                       Prob > F      =       .
                                                       R-squared     =  0.8001
                                                       Root MSE      =  .48257

                            (Std. Err. adjusted for 28 clusters in cluster_id)
------------------------------------------------------------------------------
             |               Robust
      fine_5 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       twins |  -.0019149   .0064267    -0.30   0.768    -.0151014    .0112715
       rural |   .0037172   .0035191     1.06   0.300    -.0035034    .0109377
    h_fm_han |   .0041991   .0045797     0.92   0.367    -.0051976    .0135959
             |
       order |
          2  |   .0003516   .0060938     0.06   0.954    -.0121517     .012855
          3  |  -.0005002    .009597    -0.05   0.959    -.0201916    .0191911
             |
 m_birth_age |
         17  |   .0097234   .0063619     1.53   0.138    -.0033302     .022777
         18  |   .0030901   .0070751     0.44   0.666    -.0114269    .0176071
         19  |   .0058503   .0066646     0.88   0.388    -.0078243    .0195249
         20  |   .0050639   .0068884     0.74   0.469      -.00907    .0191978
         21  |   .0057132   .0075854     0.75   0.458    -.0098507    .0212771
         22  |   .0030964   .0078554     0.39   0.697    -.0130217    .0192144
         23  |   .0014638   .0091126     0.16   0.874    -.0172337    .0201613
         24  |   .0049968   .0091671     0.55   0.590    -.0138126    .0238061
         25  |   .0069059   .0100799     0.69   0.499    -.0137764    .0275882
         26  |   .0060431   .0093199     0.65   0.522    -.0130798     .025166
         27  |   .0042689   .0105165     0.41   0.688    -.0173092    .0258469
         28  |   .0033444   .0100366     0.33   0.742     -.017249    .0239378
         29  |   .0021357    .010738     0.20   0.844    -.0198969    .0241683
         30  |   .0088914    .009255     0.96   0.345    -.0100983    .0278812
         31  |   .0077617   .0100081     0.78   0.445    -.0127733    .0282966
         32  |   .0059779   .0084794     0.70   0.487    -.0114205    .0233762
         33  |   .0108215   .0095939     1.13   0.269    -.0088635    .0305064
         34  |   .0057605   .0094635     0.61   0.548     -.013657    .0251781
         35  |    .017577   .0121037     1.45   0.158    -.0072578    .0424117
         36  |   .0207169   .0090968     2.28   0.031     .0020519     .039382
         37  |   .0318938   .0212425     1.50   0.145    -.0116921    .0754797
         38  |   .0004598   .0154301     0.03   0.976    -.0312002    .0321197
         39  |   .0378012   .0188268     2.01   0.055    -.0008282    .0764305
         40  |   .0215415   .0282946     0.76   0.453    -.0365142    .0795971
         41  |   .0132579   .0232508     0.57   0.573    -.0344488    .0609645
         42  |  -.0302512   .0413165    -0.73   0.470    -.1150257    .0545232
         43  |  -.0567474   .0470694    -1.21   0.238    -.1533258     .039831
         44  |  -.0757645   .0499165    -1.52   0.141    -.1781846    .0266557
         45  |   .1096052   .0869217     1.26   0.218    -.0687434    .2879537
         46  |   .0453205   .0500128     0.91   0.373    -.0572973    .1479382
         47  |   .0344481   .0513587     0.67   0.508    -.0709313    .1398275
         48  |  -.0131573   .0918622    -0.14   0.887     -.201643    .1753284
         49  |  -.0749022    .096105    -0.78   0.443    -.2720934    .1222889
         50  |   .0163906   .1353791     0.12   0.905    -.2613844    .2941656
             |
 birth_month |
          1  |   5.549426   .1325631    41.86   0.000     5.277429    5.821423
          2  |   5.550524   .1331771    41.68   0.000     5.277268    5.823781
          3  |   5.550029   .1326059    41.85   0.000     5.277944    5.822114
          4  |   5.548699   .1336753    41.51   0.000      5.27442    5.822978
          5  |   5.549259   .1325505    41.87   0.000     5.277288     5.82123
          6  |   5.547474   .1336915    41.49   0.000     5.273162    5.821786
          7  |   5.547415   .1336412    41.51   0.000     5.273206    5.821624
          8  |   5.549467   .1335261    41.56   0.000     5.275494     5.82344
          9  |   5.547483    .132798    41.77   0.000     5.275004    5.819962
         10  |   5.549027   .1328085    41.78   0.000     5.276526    5.821527
         11  |     5.5515   .1320634    42.04   0.000     5.280528    5.822472
         12  |   5.551617   .1322171    41.99   0.000     5.280329    5.822904
             |
        prov |
         12  |   7.510757   .0514128   146.09   0.000     7.405267    7.616248
         13  |   6.328083   .0334558   189.15   0.000     6.259438    6.396729
         14  |   7.966314   .0707926   112.53   0.000     7.821059    8.111568
         15  |   6.059096   .0147142   411.79   0.000     6.028905    6.089287
         21  |   .6057344   .0183931    32.93   0.000     .5679949     .643474
         22  |   8.010236   .0163825   488.95   0.000     7.976622     8.04385
         23  |   7.581047   .0281502   269.31   0.000     7.523287    7.638806
         31  |   1.832005   .0237143    77.25   0.000     1.783347    1.880662
         32  |   4.502713   .0168047   267.94   0.000     4.468233    4.537193
         33  |   5.404338   .0124063   435.61   0.000     5.378883    5.429794
         34  |   6.775149   .0535537   126.51   0.000     6.665266    6.885032
         35  |   3.884476   .0253398   153.30   0.000     3.832483    3.936469
         36  |   4.981208   .0336816   147.89   0.000     4.912099    5.050317
         37  |   8.084254   .0336644   240.14   0.000      8.01518    8.153327
         41  |   6.067506   .0293852   206.48   0.000     6.007212    6.127799
         42  |   4.475038   .0297387   150.48   0.000     4.414019    4.536057
         43  |   5.278821   .0512639   102.97   0.000     5.173636    5.384006
         44  |   3.916174   .0975452    40.15   0.000     3.716028    4.116321
         45  |   .2486025   .0231332    10.75   0.000     .2011371    .2960679
         51  |   5.838672   .0327606   178.22   0.000     5.771453    5.905891
         52  |   2.135296   .0655771    32.56   0.000     2.000743     2.26985
         53  |   3.796177    .094439    40.20   0.000     3.602405     3.98995
         61  |    5.52763    .067057    82.43   0.000      5.39004    5.665219
         62  |   6.397383   .1108914    57.69   0.000     6.169853    6.624914
         63  |   5.191802    .112249    46.25   0.000     4.961486    5.422118
         64  |   4.974048   .1053798    47.20   0.000     4.757826    5.190269
         65  |   3.448733    .059801    57.67   0.000     3.326032    3.571435
             |
        cell |
         18  |   .3494762   .0858718     4.07   0.000     .1732819    .5256705
         28  |   -5.56546    .132594   -41.97   0.000    -5.837521     -5.2934
         29  |  -5.214346   .1005812   -51.84   0.000    -5.420721    -5.00797
         30  |  -4.926383   .0910156   -54.13   0.000    -5.113132   -4.739634
         31  |  -4.388112   .1217124   -36.05   0.000    -4.637845   -4.138379
         32  |  -3.835315   .1579145   -24.29   0.000    -4.159329   -3.511302
         33  |  -3.268378   .1711126   -19.10   0.000    -3.619472   -2.917284
         34  |  -2.688788   .2143778   -12.54   0.000    -3.128655   -2.248921
         35  |  -2.405115   .2081904   -11.55   0.000    -2.832287   -1.977944
         36  |  -1.972515   .1933191   -10.20   0.000    -2.369173   -1.575857
         37  |   -1.66177   .1787647    -9.30   0.000    -2.028564   -1.294975
         38  |  -5.254119   .0989081   -53.12   0.000    -5.457061   -5.051176
         39  |  -4.951882   .0925381   -53.51   0.000    -5.141754   -4.762009
         40  |  -4.406431   .1230452   -35.81   0.000    -4.658899   -4.153963
         41  |  -3.815564   .1598884   -23.86   0.000    -4.143628     -3.4875
         42  |  -3.259979   .1700776   -19.17   0.000    -3.608949   -2.911009
         43  |  -2.673091   .2116697   -12.63   0.000    -3.107402   -2.238781
         44  |  -2.399555   .2076648   -11.55   0.000    -2.825648   -1.973462
         45  |  -1.960963   .1898718   -10.33   0.000    -2.350548   -1.571379
         46  |  -1.651894    .177668    -9.30   0.000    -2.016438   -1.287349
         47  |  -1.352355   .1724431    -7.84   0.000    -1.706179   -.9985311
         48  |  -.9662945   .1526095    -6.33   0.000    -1.279423   -.6531656
         49  |  -.5319251   .0691901    -7.69   0.000    -.6738914   -.3899588
         50  |   -.236754   .0532827    -4.44   0.000    -.3460811   -.1274268
         51  |   .0712397    .044087     1.62   0.118    -.0192193    .1616987
         57  |  -2.532601   .2266344   -11.17   0.000    -2.997617   -2.067586
         58  |  -2.264651   .2134184   -10.61   0.000    -2.702549   -1.826752
         59  |  -1.918737   .1894444   -10.13   0.000    -2.307445   -1.530029
         60  |  -1.603111   .1732028    -9.26   0.000    -1.958494   -1.247728
         61  |  -1.309592   .1608699    -8.14   0.000     -1.63967   -.9795147
         62  |  -.9659772   .1350432    -7.15   0.000    -1.243063   -.6888914
         63  |  -.5761251   .0529453   -10.88   0.000      -.68476   -.4674902
         64  |  -.2918991   .0280497   -10.41   0.000    -.3494524   -.2343458
         65  |          0  (omitted)
             |
   prov2Xyob |  -.4287544   .0021542  -199.03   0.000    -.4331744   -.4243343
   prov3Xyob |   -.324665   .0014604  -222.31   0.000    -.3276615   -.3216685
   prov4Xyob |  -.4313759   .0032139  -134.22   0.000    -.4379703   -.4247814
   prov5Xyob |  -.3456997   .0007196  -480.37   0.000    -.3471763   -.3442231
   prov6Xyob |  -.0291804     .00079   -36.94   0.000    -.0308013   -.0275596
   prov7Xyob |  -.4734658   .0006141  -770.97   0.000    -.4747259   -.4722058
   prov8Xyob |  -.4221152     .00115  -367.05   0.000    -.4244748   -.4197555
   prov9Xyob |  -.1475336   .0010447  -141.22   0.000    -.1496771     -.14539
  prov10Xyob |  -.2380928   .0006933  -343.43   0.000    -.2395153   -.2366703
  prov11Xyob |  -.2956195   .0004623  -639.51   0.000     -.296568    -.294671
  prov12Xyob |  -.4120982   .0022253  -185.19   0.000    -.4166641   -.4075323
  prov13Xyob |  -.2168079   .0009146  -237.06   0.000    -.2186844   -.2149314
  prov14Xyob |  -.2979494   .0012308  -242.08   0.000    -.3004748   -.2954241
  prov15Xyob |  -.4482707   .0015525  -288.75   0.000    -.4514561   -.4450853
  prov16Xyob |  -.3372429   .0012352  -273.03   0.000    -.3397773   -.3347085
  prov17Xyob |  -.2460576    .001107  -222.28   0.000     -.248329   -.2437863
  prov18Xyob |  -.3031941   .0023931  -126.69   0.000    -.3081043   -.2982838
  prov19Xyob |  -.2075246   .0044398   -46.74   0.000    -.2166342   -.1984149
  prov20Xyob |  -.0444464   .0006822   -65.15   0.000    -.0458462   -.0430467
  prov21Xyob |  -.3421834   .0012825  -266.80   0.000     -.344815   -.3395519
  prov22Xyob |  -.1662469   .0028939   -57.45   0.000    -.1721846   -.1603091
  prov23Xyob |  -.2311935   .0041508   -55.70   0.000    -.2397102   -.2226767
  prov24Xyob |  -.3243932   .0028385  -114.28   0.000    -.3302172   -.3185692
  prov25Xyob |  -.3495484   .0047872   -73.02   0.000    -.3593709   -.3397259
  prov26Xyob |  -.3194791   .0048569   -65.78   0.000    -.3294447   -.3095136
  prov27Xyob |  -.2369116   .0046452   -51.00   0.000    -.2464429   -.2273804
  prov28Xyob |  -.1819308   .0026786   -67.92   0.000    -.1874269   -.1764347
       _cons |   .7529756   .0801034     9.40   0.000     .5886171    .9173341
------------------------------------------------------------------------------

. outreg2 using "table_b1.xls", keep( twins) append dec(3)
table_b1.xls
dir : seeout

. log close 
      name:  <unnamed>
       log:  /Users/Wei/Dropbox/Twins/Restat-Twins/Data/Twins-data.log
  log type:  text
 closed on:  17 Aug 2015, 16:17:35
---------------------------------------------------------------------------------------------------------------------------
